{"dataCollections":[{"id":{"identifierType":"Fedora PID","identifier":"csiro:5862"},"dataCollectionId":5862,"self":"https://data.csiro.au/dap/ws/v2/collections/5862","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5862","fileUpload":false,"fileId":0},"title":"SRTM Grid Cell Area (3" resolution) derived from 3" SRTM DEM-S","description":"The SRTM grid cell area dataset has values of cell area in square metres.\n\nThe grid cell area product was derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 second resolution SRTM data acquired by NASA in February 2000. \n\nThe calculation of grid cell area from the DEM-S accounted for the varying spacing between grid points in the geographic projection. ","keywords":"Grid Cell Area; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 3.0 Unported Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/2","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights Reserved (including copyright) CSIRO Australia 2012.","published":"2012-11-21T18:58:11.555+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9278","doi":"10.4225/08/50AC89675E6DD","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9636"},"dataCollectionId":10029,"self":"https://data.csiro.au/dap/ws/v2/collections/10029","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9636","fileUpload":false,"fileId":0},"title":"Prescott Index derived from 1" SRTM DEM-S","description":"The Prescott Index is a measure of water balance that has proven to be a useful in soil mapping both to stratify study areas for sampling and as a quantitative predictor of soil properties (Prescott, 1949; McKenzie et al, 2000). The index was designed to give an indication of the intensity of leaching by excess water and is calculated using long-term average precipitation P and potential evaporation E, both expressed as mean monthly values in mm (mean annual values divided by 12):\n\nPI = 0.445P / E^0.75 \n\nThe evaporation was estimated from temperature and net radiation; the net radiation was computed by the SRAD solar radiation model using the smoothed 1 arc-second resolution DEM-S (ANZCW0703014016) and includes both regional climatic influences and local topographic effects. \n\nPrecipitation and temperature were obtained from national climate surfaces averaged over the same time period as the climatic information used in the radiation calculations (1981-2006).\n\nThe Prescott Index has no units. Larger values indicate wetter conditions.\n\nThe 3 arc-second resolution version of the Prescott Index has been produced from the 1 arc-second resolution surface, by aggregating the cells in a 3x3 window and taking the mean value.","keywords":"Prescott Index; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 3.0 Unported Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/2","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO Australia 2012.","published":"2014-08-13T22:54:53.327+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/14035","doi":"10.4225/08/53EB2D0EAE377","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10548"},"dataCollectionId":10548,"self":"https://data.csiro.au/dap/ws/v2/collections/10548","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10548","fileUpload":false,"fileId":0},"title":"Maps of clay minerals - kaolinite, illite and smectite in Australian soils","description":"Clay minerals are the most reactive inorganic components of soils. They help to determine soil properties and largely govern their behaviors and functions. Clay minerals also play important roles in biogeochemical cycling and interact with the environment to affect geomorphic processes such as weathering, erosion and deposition. This data provides new spatially explicit clay mineralogy information for Australia that will help to improve our understanding of soils and their role in the functioning of landscapes and ecosystems. I measured the abundances of kaolinite, illite and smectite in Australian soils using near infrared (NIR) spectroscopy. Using a model-tree algorithm, I built rule-based models for each mineral at two depths (0-20 cm, 60-80 cm) as a function of predictors that represent the soil-forming factors (climate, parent material, relief, vegetation and time), their processes and the scales at which they vary. The results show that climate, parent material and soil type exert the largest influence on the abundance and spatial distribution of the clay minerals; relief and vegetation have more local effects. I digitally mapped each mineral on a 3 arc-second grid. The maps show the relative abundances and distributions of kaolinite, illite and smectite in Australian soils. Kaolinite occurs in a range of climates but dominates in deeply weathered soils, in soils of higher landscapes and in regions with more rain. Illite is present in varied landscapes and may be representative of colder, more arid climates, but may also be present in warmer and wetter soil environments. Smectite is often an authigenic mineral, formed from the weathering of basalt, but it also occurs on sediments and calcareous substrates. It occurs predominantly in drier climates and in landscapes with low relief. These new clay mineral maps fill a significant gap in the availability of soil mineralogical information. They provide data to for example, assist with research into soil fertility and food production, carbon sequestration, land degradation, dust and climate modeling and paleoclimatic change.\n\nAttributes: \nUnits of measurement: \n1.\tAbundance of kaolin (0 - 1) for the 0-20 cm and 60-80 cm depths; \n2.\tAbundance of illite (0 - 1) for the 0-20 cm and 60-80 cm depths; \n3.\tAbundance of smectite (0 - 1) for the 0-20 cm and 60-80 cm depths; \n4.\tTernary RGB image of mineral composition for the 0-20 cm and 60-80 cm depths. \n\nFor details please see Viscarra Rossel (2011).\n\nData Type: Float Grid. \nKaolinite, illite, smectite composite maps in GEOTIFF format. \n\nMap projections: Geographic. \n\nDatum: GDA94 \n\nMap units: Decimal degrees. \n\nResolution: 0.00083333333 degrees. \n\nFile Header Information: \nncols 48874; \nnrows 40373; \nxllcorner 112.91246795654; \nyllcorner -43.642475129116; \ncellsize 0.00083333333333333; \nNODATA_value -9999; \nbyteorder LSBFIRST.","keywords":"TERN_Soils; TERN_Soils_DSM; clay minerals; digital soil mapping; near infrared; predictive spatial modelling","licence":"Creative Commons Attribution 3.0 Unported Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/2","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO Australia 2014.","published":"2015-08-28T20:22:26.048+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":[],"andsPid":"102.100.100/23000","doi":"10.4225/08/55DFFCA4715D8","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10588"},"dataCollectionId":10588,"self":"https://data.csiro.au/dap/ws/v2/collections/10588","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10588","fileUpload":false,"fileId":0},"title":"Maps of Australian soil composition measured with visible-near infrared spectra","description":"We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer. These spectra provide an integrative measure that provides information on the fundamental characteristics and composition of the soil, including colour, iron oxide, clay and carbonate mineralogy, organic matter content and composition, the amount of water present and particle size. This soil information content of the spectra was summarised using a principal component analysis (PCA). We used model trees to derive statistical relationships between the scores of the PCA and 31 predictors that were readily available and we thought might best represent the factors of soil formation (climate, organisms, relief, parent material, time and the soil itself). The models were validated and subsequently used to produce digital maps of the information content of the spectra, as summarised by the PCA, with estimates of prediction error at 3-arc seconds (around 90 m) pixel resolution. The maps might be useful in situations requiring high-resolution, quantitative soil information e.g. in agricultural, environmental and ecologic modelling and for soil mapping and classification.\n\nAttributes: \nUnits of measurement: \n1.\tPrincipal component 1; \n2.\tPrincipal component 3; \n3.\tPrincipal component 3. \n\nFor interpretations please see Viscarra Rossel & Chen (2011). \n\nData Type: Float Grid. \n\nMap Projection: Geographic. \n\nDatum: GDA94. \n\nMap units: Decimal degrees. \n\nResolution: 0.00083333333 degrees. \n\nFile Header Information:\nncols 48874; \nnrows 40373; \nxllcorner 112.91246795654; \nyllcorner -43.642475129116; \ncellsize 0.00083333333333333; \nNODATA_value -9999; \nbyteorder LSBFIRST. ","keywords":"TERN_Soils; TERN_Soils_DSM; Soil visible-near infrared spectra; Digital soil mapping; Soil mapping; Principal components analysis; Predictive modelling; Soil-landscape modelling","credit":"This project was conducted with funding from the Australian Collaborative Land Evaluation Program (ACLEP).","licence":"Creative Commons Attribution 3.0 Unported Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/2","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO Australia 2014.","published":"2015-08-28T20:11:38.397+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen"],"andsPid":"102.100.100/23001","doi":"10.4225/08/55DFFCA48F284","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10608"},"dataCollectionId":10608,"self":"https://data.csiro.au/dap/ws/v2/collections/10608","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10608","fileUpload":false,"fileId":0},"title":"Maps of iron oxides and the color of Australian soil","description":"Iron (Fe) oxide mineralogy in most Australian soils is poorly characterized, even though Fe oxides play an important role in soil function. Fe oxides reflect the conditions of pH, redox potential, moisture, and temperature in the soil environment. The strong pigmenting effect of Fe oxides gives most soils their color, which is largely a reflection of the soil’s Fe mineralogy. Visible-near-infrared (vis-NIR) spectroscopy can be used to identify and measure the abundance of certain Fe oxides in soil, and the visible range can be used to derive tristimuli soil color information. We measured the spectra of 4606 surface soil samples from across Australia using a vis-NIR spectrometer with a wavelength range of 350-2500 nm. We determined the Fe oxide abundance for each sample using the diagnostic absorption features of hematite (near 880 nm) and goethite (near 920 nm) and derived a normalized iron oxide difference index (NIODI) to better discriminate between them. The NIODI was generalized across Australia with its spatial uncertainty using sequential indicator simulation, which resulted in a map of the probability of the occurrence of hematite and goethite. We also derived soil RGB color from the spectra and mapped its distribution and uncertainty across the country using sequential Gaussian simulations. The simulated RGB color values were made into a composite true color image and were also converted to Munsell hue, value, and chroma. These color maps were compared to the map of the NIODI, and both were used to interpret our results. The maps were validated by randomly splitting the data into training and test data sets, as well as by comparing our results to existing studies on the distribution of Fe oxides in Australian soils.\nAttributes: \nUnits of measurement: \n1.\tMunsell Hue; \n2.\tMunsell Chroma; \n3.\tMunsell value; \n4.\tNIODI; \n5.\tNIODI uncertainty.\nFor details please see Viscarra Rossel et al. (2010). \n\nData Type: Float Grid. \n\nMap projection: Lambert Conformal Conic. \n\nDatum: GDA94. \n\nMap units: Decimal degrees. \n\nResolution: 10,000 metres. \n\nFile Header Information:\nncols 392; \nnrows 361; \nxllcorner -2032461.3; \nyllcorner -4936305.3; \ncellsize 10000; \nNODATA_value -9999; \nbyteorder LSBFIRST.","keywords":"TERN_Soils; TERN_Soils_DSM; hematite; goethite; soil color; soil colour; visible-near-infrared reflectance; soil mapping; geostatistical simulations","credit":"This project was conducted with funding from the Australian Collaborative Land Evaluation Program (ACLEP).","licence":"CSIRO Data Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1061","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO Australia 2014.","published":"2015-08-28T16:15:30.953+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Elisabeth Bui","Patrice de Caritat","Neil McKenzie"],"andsPid":"102.100.100/22999","doi":"10.4225/08/55DFFC6C56916","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5142"},"dataCollectionId":15971,"self":"https://data.csiro.au/dap/ws/v2/collections/15971","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5142","fileUpload":false,"fileId":0},"title":"Slope derived from 1" SRTM DEM-S","description":"Slope measures the inclination of the land surface from the horizontal. The percent slope and degrees slope products represent this inclination as the ratio of change in height to distance.\n\nThe slope (percentage) and slope (degrees) products were derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 second resolution SRTM data acquired by NASA in February 2000. The calculation of slope from DEM-S accounted for the varying spacing between grid points in the geographic projection. \n\nThe 3 second resolution slope products were generated from the 1 second percent slope/degrees slope products and masked by the 3” water and ocean mask datasets.\n","keywords":"Slope; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-01-04T17:21:11.204+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/8341","doi":"10.4225/08/5689DA774564A","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5037"},"dataCollectionId":16671,"self":"https://data.csiro.au/dap/ws/v2/collections/16671","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5037","fileUpload":false,"fileId":0},"title":"Aspect derived from 1" SRTM DEM-S","description":"Aspect measures the direction in which a land surface slope faces. The direction is expressed in degrees from north.\n\nThe aspect products were derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. The calculation of aspect from DEM-S accounted for the varying spacing between grid points in the geographic projection. \n\nThe aspect data are available at 1 arc-second and 3 arc-second resolution\n\nThe 3” resolution version of the aspect product has been masked by the 3” water and ocean mask datasets.","keywords":"Aspect; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-03-03T12:10:42.001+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/8340","doi":"10.4225/08/56D778315A62B","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5591"},"dataCollectionId":16712,"self":"https://data.csiro.au/dap/ws/v2/collections/16712","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5591","fileUpload":false,"fileId":0},"title":"Plan Curvature derived from 1" SRTM DEM-S","description":"Plan (or contour) curvature is the rate of change of aspect (orthogonal to the slope) and represents topographic convergence or divergence. It is significant for water movement across the landscape, i.e., the accumulation or dispersion of water.\n\nThe plan curvature products were derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 second resolution SRTM data acquired by NASA in February 2000. The calculation of plan curvature from DEM-S accounted for the varying spacing between grid points in the geographic projection. \n\nThe plan curvature data are available at 1 arc-second (approx. 30 m) and 3 arc-second (approx. 90 m) resolutions.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second plan curvature product and masked by the 3” water and ocean mask datasets.","keywords":"Plan Curvature; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-03-08T20:11:25.813+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9239","doi":"10.4225/08/56DE806D91E44","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5681"},"dataCollectionId":16730,"self":"https://data.csiro.au/dap/ws/v2/collections/16730","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5681","fileUpload":false,"fileId":0},"title":"Multi-resolution Valley Bottom Flatness (MrVBF)","description":"MrVBF is a topographic index designed to identify areas of deposited material at a range of scales based on the observations that valley bottoms are low and flat relative to their surroundings and that large valley bottoms are flatter than smaller ones. Zero values indicate erosional terrain with values 1 and larger indicating progressively larger areas of deposition. There is some evidence that MrVBF values correlate with depth of deposited material.\n\nThis collection includes 1 arc-second and 3 arc-second resolution versions of MrVBF.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second MrVBF product and masked by the 3” water and ocean mask datasets.\n","keywords":"MrVBF; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-04-04T12:39:33.934+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Trevor Dowling","Jenet Austin"],"andsPid":"102.100.100/9236","doi":"10.4225/08/5701C885AB4FE","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5595"},"dataCollectionId":16731,"self":"https://data.csiro.au/dap/ws/v2/collections/16731","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5595","fileUpload":false,"fileId":0},"title":"Median of Percent Slope over 300 m derived from 1" SRTM DEM-S","description":"Slope measures the inclination of the land surface from the horizontal. Percent slope represents this inclination as the ratio of change in height to distance. The focal median of percent slope can be used as a surrogate for modal slope in landform pattern analysis.\n\nThe 300 m focal median percent slope product was derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. The calculation of focal median slope from percent slope accounted for the varying spacing between grid points in the geographic projection.\n\nThis collection includes Median of Percent Slope (over 300 m) at 1 arc-second and 3 arc-second resolutions.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second 300 m focal median of percent slope product and masked by the 3” water and ocean mask datasets.","keywords":"Median of Percent Slope; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-03-08T21:49:08.496+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9235","doi":"10.4225/08/56DE9747E897E","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:6239"},"dataCollectionId":16772,"self":"https://data.csiro.au/dap/ws/v2/collections/16772","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:6239","fileUpload":false,"fileId":0},"title":"Multi-resolution Ridge Top Flatness (MrRTF)","description":"MrRTF is a topographic index designed to identify high flat areas at a range of scales. It complements the MrVBF index that is designed to identify areas of deposited material in flat valley bottoms. Unlike MrVBF, the MrRTF index does not have a clear link to landform processes but it has been found to be a useful adjunct to MrVBF in landform classification. Zero values indicate areas that are steep or low, with values 1 and larger indicating progressively larger areas of high flat land. \n\nThis collection includes MrRTF data at 1 arc-second and 3 arc-second resolutions.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second MrRTF product and masked by the 3” water and ocean mask datasets.\n","keywords":"MrRTF; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2013.","rights":"All Rights (including copyright) CSIRO 2013.","published":"2016-03-17T17:01:17.103+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Trevor Dowling","Jenet Austin"],"andsPid":"102.100.100/10846","doi":"10.4225/08/56EA312A5E63B","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5592"},"dataCollectionId":16790,"self":"https://data.csiro.au/dap/ws/v2/collections/16790","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5592","fileUpload":false,"fileId":0},"title":"Profile Curvature derived from 1" SRTM DEM-S","description":"Profile curvature is the rate of change of potential gradient down a flow line and represents the changes in flow velocity down a slope. It is significant for flow acceleration, erosion/deposition rates and geomorphology.\n\nThe profile curvature product was derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. The calculation of profile curvature from DEM-S accounted for the varying spacing between grid points in the geographic projection. \n\nThis collection includes Profile Curvature data at 1 arc-second and 3 arc-second resolutions.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second profile curvature product and masked by the 3” water and ocean mask datasets.","keywords":"Profile Curvature; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-03-17T11:25:11.627+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9240","doi":"10.4225/08/56E9DEBF65706","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5590"},"dataCollectionId":16810,"self":"https://data.csiro.au/dap/ws/v2/collections/16810","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5590","fileUpload":false,"fileId":0},"title":"Relief - Elevation Range over 1000 m derived from 1" SRTM DEM-S","description":"The elevation range measures the full range of elevations within a circular window and can be used as a representation of local relief. \n\nThe 1000 m elevation range product was derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. \n\nThis collection includes Relief data at 1 arc-second and 3 arc-second resolutions.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second 1000 m elevation range product and masked by the 3” water and ocean mask datasets.","keywords":"Relief; Elevation Range; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-03-17T09:31:16.832+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9233","doi":"10.4225/08/56E9C8DDD664D","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5589"},"dataCollectionId":16813,"self":"https://data.csiro.au/dap/ws/v2/collections/16813","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5589","fileUpload":false,"fileId":0},"title":"Relief - Elevation Range over 300 m derived from 1" SRTM DEM-S","description":"The elevation range measures the full range of elevations within a circular window and can be used as a representation of local relief. \n\nThe 300 m elevation range product was derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. \n\nThis collection includes data at 1 arc-second and 3 arc-second resolutions.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second 300 m elevation range product and masked by the 3” water and ocean mask datasets.","keywords":"Relief; Elevation Range; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-06-07T15:27:09.235+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9234","doi":"10.4225/08/57511C7CBC340","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5587"},"dataCollectionId":16891,"self":"https://data.csiro.au/dap/ws/v2/collections/16891","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5587","fileUpload":false,"fileId":0},"title":"Contributing Area - Multiple Flow Direction (Partial) derived from 1" SRTM DEM-H","description":"CA_MFD_PARTIAL is contributing area in m2 computed using multiple flow directions on hillslopes and ANUDEM-derived flow directions in channels. The contributing area was computed on 1 degree tiles with 200 cell (about 5 km) overlaps so the areas in channels do not account for catchments beyond that size (hence the use of PARTIAL in the name). The primary purpose of this product was to calculate topographic wetness index (TWI; Gallant and Wilson, 2000) for which full contributing areas in channels are not necessary. Do not use this product to represent contributing areas of catchments larger than 5 km across.\n\nThe CA_MFD_PARTIAL product was derived from the Hydrologically enforced Digital Elevation Model (DEM-H; ANZCW0703014615), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. \n\nThis data is available in tiled format at 1 arc-second and 3 arc-second resolution.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second CA_MFD (partial) product and masked by the 3” water and ocean mask datasets.\n","keywords":"Contributing Area; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-06-07T13:54:35.431+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9237","doi":"10.4225/08/57511C42603DF","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5588"},"dataCollectionId":18070,"self":"https://data.csiro.au/dap/ws/v2/collections/18070","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5588","fileUpload":false,"fileId":0},"title":"Topographic Wetness Index derived from 1" SRTM DEM-H","description":"Topographic Wetness Index (TWI) is calculated as log_e(specific catchment area / slope) and estimates the relative wetness within a catchment.\n\nThe TWI product was derived from the partial contributing area product (CA_MFD_PARTIAL), which was computed from the Hydrologically enforced Digital Elevation Model (DEM-H; ANZCW0703014615), and from the percent slope product, which was computed from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016). Both DEM-S and DEM-H are based on the 1 arcsecond resolution SRTM data acquired by NASA in February 2000.\n\nNote that the partial contributing area product does not always represent contributing areas larger than about 25 km2 because it was processed on overlapping tiles, not complete catchments. This only impacts TWI values in river channels and does not affect values on the land around the river channels. Since the index is not intended for use in river channels this limitation has no impact on the utility of TWI for spatial modelling.\n\nThe TWI data are available in gridded format at 1 arcsecond and 3 arcsecond resolutions.\n\nThe 3 arcsecond resolution TWI product was generated from the 1 arcsecond TWI product and masked by the 3” water and ocean mask datasets.","keywords":"Topographic Wetness Index; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-06-09T23:32:21.478+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9241","doi":"10.4225/08/57590B59A4A08","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9632"},"dataCollectionId":18098,"self":"https://data.csiro.au/dap/ws/v2/collections/18098","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9632","fileUpload":false,"fileId":0},"title":"Mean monthly incoming atmospheric longwave radiation modelled using the 1" DEM-S - 1" tiles","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as 1x1 degree tiles in ESRI float grid format. 813 tiles make up the extent of Australia. The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18491 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18492","keywords":"Monthly incoming longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2016-07-19T19:55:11.074+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/14037","doi":"10.4225/08/578D8B9BC1211","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9633"},"dataCollectionId":18153,"self":"https://data.csiro.au/dap/ws/v2/collections/18153","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9633","fileUpload":false,"fileId":0},"title":"Mean monthly net longwave radiation modelled using the 1" DEM-S - 1" tiles","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as 1x1 degree tiles in ESRI float grid format. 813 tiles make up the extent of Australia. The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18611 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18612","keywords":"Monthly net longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2016-07-28T00:14:34.071+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/14040","doi":"10.4225/08/579844E1234E3","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9630"},"dataCollectionId":18190,"self":"https://data.csiro.au/dap/ws/v2/collections/18190","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9630","fileUpload":false,"fileId":0},"title":"Mean monthly net radiation modelled using the 1" DEM-S - 1" tiles","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as 1x1 degree tiles in ESRI float grid format. 813 tiles make up the extent of Australia. The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18670 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18671","keywords":"Monthly net radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2016-07-28T19:47:02.570+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/14036","doi":"10.4225/08/57995A613EB22","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9631"},"dataCollectionId":18250,"self":"https://data.csiro.au/dap/ws/v2/collections/18250","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9631","fileUpload":false,"fileId":0},"title":"Mean monthly shortwave radiation ratio modelled using the 1" DEM-S - 1" tiles","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as 1x1 degree tiles in ESRI float grid format. 813 tiles make up the extent of Australia. The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18731 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18732","keywords":"Monthly shortwave radiation ratio; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2016-07-29T19:48:50.731+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/14042","doi":"10.4225/08/579AA85D210E7","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18335"},"dataCollectionId":18450,"self":"https://data.csiro.au/dap/ws/v2/collections/18450","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18335","fileUpload":false,"fileId":0},"title":"Mean monthly outgoing surface longwave radiation modelled using the 1" DEM-S - 1" tiled data","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe data in this collection are available at 1 arcsecond resolution as 1x1 degree tiles. 813 tiles make up the extent of Australia.\n\nThe 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9634 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18336","keywords":"Monthly outgoing longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2016-07-05T14:35:07.950+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39411","doi":"10.4225/08/577A03CC7E4B7","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9530"},"dataCollectionId":18850,"self":"https://data.csiro.au/dap/ws/v2/collections/18850","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9530","fileUpload":false,"fileId":0},"title":"Mean monthly total shortwave radiation on a sloping surface modelled using the 1" DEM-S - 1" tiles","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as 1x1 degree tiles in ESRI float grid format. 813 tiles make up the extent of Australia. The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18851 .\n\nThe 3 arc-second resolution versions of these radiation surfaces have been produced from the 1 arc-second resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18852","keywords":"Monthly shortwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2016-08-09T22:38:09.715+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/14034","doi":"10.4225/08/57A96416E93EE","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5593"},"dataCollectionId":19071,"self":"https://data.csiro.au/dap/ws/v2/collections/19071","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5593","fileUpload":false,"fileId":0},"title":"Slope Relief Classification derived from 1" SRTM DEM-S","description":"Slope relief landform pattern classification based on Speight (2009).\n\nThe slope relief product was derived from the 300 m focal median percent slope product, and the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. \n\nThe slope relief classification dataset is available in 1 arc-second and 3 arc-second resolutions.\n\nThe 3 arc-second resolution product was generated from the 1 arc-second slope relief product and masked by the 3” water and ocean mask datasets.","keywords":"Slope Relief; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2016-08-11T13:08:05.249+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/9238","doi":"10.4225/08/57512079C1A93","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:19354"},"dataCollectionId":19354,"self":"https://data.csiro.au/dap/ws/v2/collections/19354","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:19354","fileUpload":false,"fileId":0},"title":"Maps of Australian soil loss by water erosion derived using the RUSLE","description":"The Revised Universal Soil Loss Equation (RUSLE) estimates the annual soil loss that is due to erosion using a factor-based approach with rainfall, soil erodibility, slope length, slope steepness and cover management and conservation practices as inputs. The collection is (i) a set of maps that represent the RUSLE factors, (ii) a map of the RUSLE estimates of soil erosion in Australia and (iii) a map of the uncertainty in the estimates of erosion.","keywords":"Soil erosion; RUSLE; Visible-near infrared spectra; Earth observation; Digital soil mapping; Water erosion; Modelling","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2016.","rights":"All Rights (including copyright) CSIRO 2016.","published":"2016-11-17T10:44:26.326+11:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Hongfen Teng","Shi Zhou","Thorsten Behrens","Adrian Chappell","Elisabeth Bui"],"andsPid":"102.100.100/42082","doi":"10.4225/08/582cef2dd5966","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10856"},"dataCollectionId":29995,"self":"https://data.csiro.au/dap/ws/v2/collections/29995","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10856","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid Digital Soil Property Maps for Western Australia (3" resolution)","description":"These are products of the Soil and Landscape Grid of Australia Facility generated through disaggregation of the Western Australian soil mapping. There are 9 soil attribute products available from the Soil Facility: Available Water Holding Capacity - Volumetric (AWC); Bulk Density - Whole Earth (BDw); Bulk Density - Fine Earth (BDf); Clay (CLY); Course Fragments (CFG); Electrical Conductivity (ECD); pH Water (pHw); Sand (SND); Silt (SLT).\n\nEach soil attribute product is a collection of 6 depth slices. Each depth raster has an upper and lower uncertainty limit raster associated with it. The depths provided are 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm & 100-200cm, consistent with the Specifications of the GlobalSoilMap.\n\nThe DSMART tool (Odgers et al. 2014) tool was used in a downscaling process to translate legacy soil landscape mapping to 3” resolution (approx. 100m cell size) raster predictions of soil classes (Holmes et al. Submitted). The soil class maps were then used to produce corresponding soil property surfaces using the PROPR tool (Odgers et al. 2015; Odgers et al. Submitted). Legacy mapping was compiled for the state of WA from surveys ranging in map scale from 1:20,000 to 1:2,000,000 (Schoknecht et al., 2004). The polygons are attributed with the soils and proportions of soils within polygons however individual soils were not explicitly spatially defined. These new disaggregated map products aim to incorporate expert soil surveyor knowledge embodied in legacy polygon soil maps, while providing re-interpreted soil spatial information at a scale that is more suited to on-ground decision making. \n\nNote: The DSMART-derived dissagregated legacy soil mapping products provide different spatial predictions of soil properties to the national TERN Soil Grid products derived by Cubist (data mining) and kriging based on site data by Viscarra Rossel et al. (Submitted). Where they overlap, the national prediction layers and DSMART products can be considered complementary predictions. They will offer varying spatial reliability (/ uncertainty) depending on the availability of representative site data (for national predictions) and the scale and expertise of legacy mapping. The national predictions and DSMART disaggregated layers have also been merged as a means to present the best available (lowest statistical uncertainty) data from both products (Clifford et al. In Prep).\n\nPrevious versions of this collection contained Depths layers. These have been removed as the units do not comply with Global Soil Map specifications.","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Western Australia; DSM; Global Soil Map; spatial modelling; 3-dimensional soil mapping; spatial uncertainty; DSMART; disaggregated; Available Water Capacity; Bulk Density; Clay; Electrical Conductivity; Effective Cation Exchange Capacity; Coarse Fragments; Organic Carbon; pH; Sand; Silt; EC; ECEC; BD; pH - Water; SLGA","credit":"Access to this data has been made possible by CSIRO, and the Terrestrial Ecosystem Research Network (TERN) which is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, and by agreement from the data custodians of the background data.\nThis dataset has been produced with significant input from the Department of Agriculture and Food, Western Australia, CSIRO, and the University of Sydney. \n","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2018-03-19T17:14:10.100+11:00","leadResearcher":"Karen Holmes","serviceCount":0,"contributors":["Ted Griffin","Nathan Odgers"],"andsPid":"102.100.100/16122","doi":"10.4225/08/5aaf364c54ccf","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10516"},"dataCollectionId":30034,"self":"https://data.csiro.au/dap/ws/v2/collections/30034","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10516","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid Digital Soil Property Maps for South Australia (3" resolution)","description":"These products are derived from disaggregation of legacy soil mapping in the agricultural zone of South Australia using the DSMART tool (Odgers et al. 2014a); produced for the Soil and Landscape Grid of Australia Facility. There are 10 soil attribute products available from the Soil Facility: Available Water Capacity (AWC); Bulk Density - Whole Earth (BDw); Cation Exchange Capacity (CEC); Clay (CLY); Coarse Fragments (CFG); Electrical Conductivity (ECD); Organic Carbon (SOC); pH - CaCl2( pHc); Sand (SND); Silt (SLT). \n\nEach soil attribute product is a collection of 6 depth slices (except for effective depth and total depth). Each depth raster has an upper and lower uncertainty limit raster associated with it. The depths provided are 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm & 100-200cm, consistent with the specifications of the GlobalSoilMap.\n\nThe DSMART tool was used in a downscaling process to translate legacy soil landscape mapping to 3” resolution (approx. 100m cell size) raster predictions of soil classes and corresponding soil properties. Legacy mapping was performed at 1:50,000 and 1:100,000 scales to delineate associated soils within polygons however individual soils were not explicitly spatially defined. These new disaggregated map products aim to incorporate expert soil surveyor knowledge embodied in legacy polygon soil maps, while providing re-interpreted soil spatial information at a scale that is more suited to on-ground decision making.\n\nNote: The DSMART-derived dissagregated legacy soil mapping products provide different spatial predictions of soil properties to the national TERN Soil Grid products derived by Cubist (data mining) kriging based on site data by Viscarra Rossel et al. (2014). Where they overlap, the national prediction layers and DSMART products can be considered complementary predictions. They will offer varying spatial reliability (/ uncertainty) depending on the availability of representative site data (for national predictions) and the scale and expertise of legacy mapping. The national predictions and DSMART disaggregated layers have also been merged as a means to present the best available (lowest statistical uncertainty) data from both products (Clifford et al. 2014).\n\nPrevious versions of this collection contained Depths layers. These have been removed as the units do not comply with Global Soil Map specifications.","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; South Australia; DSM; Global Soil Map; spatial modelling; 3-dimensional soil mapping; spatial uncertainty; DSMART; disaggregated; Available Water Capacity; Bulk Density; Bulk Density - Whole Earth; Cation Exchange Capacity; Clay; Coarse Fragments; Electrical Conductivity; Organic Carbon; pH - CaCl2; Sand; Silt; BD; pH; ECEC; EC; SLGA","credit":"Access to this data has been made possible by CSIRO, and the Terrestrial Ecosystem Research Network (TERN) which is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, and by agreement from the data custodians of the background data.\nThis dataset has been produced with significant input from CSIRO; South Australia Department of Environment, Water and Natural Resources; and the University of Sydney.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2018-03-19T15:44:37.477+11:00","leadResearcher":"Craig Liddicoat","serviceCount":0,"contributors":["Karen Holmes","David Maschmedt","Jan Rowland","Ross Searle","Nathan Odgers"],"andsPid":"102.100.100/16127","doi":"10.4225/08/5aaf39ed26044","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:11379"},"dataCollectionId":30093,"self":"https://data.csiro.au/dap/ws/v2/collections/30093","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:11379","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid Australia-Wide 3D Soil Property Maps (3" resolution) - Release 1","description":"The Soil Facility produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nAttributes included: \nAvailable Water Capacity; \nBulk Density - Whole Earth; \nClay;\nEffective Cation Exchange Capacity;\npH - CaCl2; \nSilt; \nSand; \nTotal Nitrogen; \nTotal Phosphorus.\n\nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 3.0 (CC By); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Bulk Density; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; Effective Cation Exchange Capacity; Available Water Capacity; Bulk Density - Whole Earth; Clay; pH - CaCl2; Silt; Sand; Total Nitrogen; Total Phosphorus; ECEC; AWC; BD; pH; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2018-03-19T23:25:17.170+11:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford"],"andsPid":"102.100.100/19200","doi":"10.4225/08/5aaf553b63215","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:30413"},"dataCollectionId":30413,"self":"https://data.csiro.au/dap/ws/v2/collections/30413","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:30413","fileUpload":false,"fileId":0},"title":"Update of the Australian Soil Classification orders map with visible-near infrared spectroscopy and digital soil class mapping","description":"Traditional soil maps have helped us to better understand soil, to form our concepts and to teach and transfer our ideas about it, and so they have been used for many purposes. Although, soil maps are available in many countries, there is a need for them to be updated because they are often deficient in that their spatial delineations and their descriptions are subjective and lack assessments of uncertainty. Updating them is a priority for federal soil surveys worldwide as well as for research, teaching and communication. New data from sensors and quantitative ‘digital’ methods provide us with the tools to do so. Here, we present an approach to update large scale, national soil maps with data derived from a combination of traditional soil profile classifications, classifications made with visible–near infrared (vis–NIR) spectroscopy, and digital soil class mapping (DSM). Our results present an update of the Australian Soil Classification (ASC) orders map. The overall error rate of the DSM model, tested on an independent validation set, was 55.6%, and a few of the orders were poorly classified. We discuss the possible reasons for these errors, but argue that compared to the previous ASC maps, our classification was derived objectively, using currently best available data sets and methods, the classification model was interpretable in terms of the factors of soil formation, the modelling produced a 1×1 km resolution soil map with estimates of spatial uncertainty for each soil order and our map has no artefacts at state and territory borders.","keywords":"TERN_Soils; TERN_Soils_DSM; Soil visible-near infrared spectra; Digital soil mapping; Soil mapping; Soil classification; Random forests ","credit":"We thank the CSIRO and the Terrestrial Ecosystem Research Network's (TERN) Soil and Landscape Grid of Australia project for collating data into the National Soil Data Collation. We are grateful to the custodians of the soil site data in each state and territory for providing access to them. They are the Queensland Department of Science, Information Technology, Innovation and the Arts, Northern Territory Department of Land Resource Management, Western Australia Department of Agriculture and Food, South Australia Department of Environment, Water and Natural Resources, Victoria Department of Environment and Primary Industries, NSW Office of Environment and Heritage, Tasmania Department Primary Industries, Parks, Water and Environment, and Geoscience Australia.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2018.","rights":"All Rights (including copyright) CSIRO 2018.","published":"2018-03-28T15:58:38.147+11:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Hongfen Teng","Shi Zhou","Behrens Thorsten"],"andsPid":"102.100.100/70024","doi":"10.4225/08/5abb208d8de9f","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:39442"},"dataCollectionId":39442,"self":"https://data.csiro.au/dap/ws/v2/collections/39442","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:39442","fileUpload":false,"fileId":0},"title":"Direct climate change impacts on growth and drought risk in blue gum (Eucalyptus globulus) and radiata pine (Pinus radiata) plantations in Australia","description":"Geolocated data points of productivity of blue gum (Eucalyptus globulus) and radiata pine (Pinus radiata) under different future climate scenarios and differing assumptions of soil depth, soil nutrition and response of vegetation to elevated CO2.","keywords":"climate change impacts, modelling, adaptation, mortality","credit":"Forest and Wood Products Australia (PR228-1011)","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2017.","rights":"All Rights (including copyright) CSIRO 2017.","published":"2022-10-07T15:54:27.571+11:00","leadResearcher":"Michael Battaglia","serviceCount":0,"contributors":["Jody Bruce"],"andsPid":"102.100.100/447277","doi":"10.25919/1k42-4434","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:20912"},"dataCollectionId":40018,"self":"https://data.csiro.au/dap/ws/v2/collections/40018","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:20912","fileUpload":false,"fileId":0},"title":"3D Mineral mapping of Queensland - Version 2 ASTER and related geoscience products","description":"The digital 3-dimenional (3D) mineral mapping suite of Queensland comprises ~20 “standardized” products at the spectral resolution of the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) sensor and generated from publicly-available satellite, airborne, field and drill core spectral data spanning the visible near infrared (VNIR; 0.4 to 1.0 µm), shortwave infrared (SWIR; 1.0 to 2.5 µm) and thermal infrared (TIR; 7.5 to 12.0 µm) wavelength regions, including: \n1.\tSatellite ASTER maps at both 30 m and 90 m pixel resolution with complete coverage of the state of Queensland, i.e. 1.853 million km²; \n2.\tAirborne HyMap maps at ~5 m pixel resolution with a coverage of ~25,000 km2 from areas across north Queensland;\n3.\tField point samples (~300) from the National Geochemical Survey of Australia (NGSA) collected from a depth of 0-10 cm of flood overbank sediments;\n4.\tDrill-core profiles (~20) of the National Virtual Core Library (NVCL) selected from the area around the Georgetown seismic line (07GA-IG2).\nKey to the processing of the remote sensing data-sets (ASTER and HyMap) was the implementation of unmixing methods to remove the effects dry and green vegetation. This unmixing was not applied to the Australian ASTER geoscience maps released in 2012 (called here Version 1 or V1) resulting in extensive areas with little/no mineral information because of the need to apply masks. The vegetation unmixing methods used in the Version 2 (V2) processing of the ASTER and HyMap imagery has resulted in very few areas without coherent mineral information. \nThe resultant V2 “mineral group” products were designed to measure mineral information potentially useful for mapping: (i) primary rock composition; (ii) superimposed alteration effects; and (iii) regolith cover. These V2 products may assist in mapping soil properties and groundwater conditions. However their relatively low spectral resolution (based on ASTER’s 14 VNIR-SWIR-TIR bands) means that they do not provide the high level of mineralogical detail available from hyperspectral systems (>100 spectral bands), like HyMap and the HyLogger. Nevertheless, the relatively low spectral resolution of ASTER means that all other sensor data can be spectrally resampled to that resolution. Furthermore, the ASTER global data archive, which now spans entire Earth’s land surface <80degrees latitude, means that it can be used as global base-map for integrating all other spectral data. \n","keywords":"Mineral mapping; 3D; ASTER; HyMap; NVCL; NGSA;vegetation unmixiing; Geology; Alteration; Regolith; Queensland; Australia; Version 2","credit":"All the derived geoscience products were developed as part of a collaborative project between the CSIRO and the Geological Survey of Queensland. This project was funded by the Geological Survey of Queensland as part of the Industry Priorities Initiative, under the Future Resources Program of the Queensland Government, as well as CSIRO Minerals. Access to NGSA samples was provided through the help of Patrice de Caritat and Matilda Thomas from Geoscience Australia. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO, Geological Survey of Queensland 2017.","rights":"All Rights (including copyright) CSIRO, Geological Survey of Queensland 2017.","published":"2019-12-06T01:08:05.653+11:00","leadResearcher":"Tom Cudahy","serviceCount":0,"contributors":["Mal Jones","Vladimir A. Lisitsin","Mike Caccetta","Simon Collings","Roger Bateman"],"andsPid":"102.100.100/44156","doi":"10.25919/5de850a1d2172","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:19311"},"dataCollectionId":42018,"self":"https://data.csiro.au/dap/ws/v2/collections/42018","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:19311","fileUpload":false,"fileId":0},"title":"Fractional cover - MODIS, CSIRO algorithm","description":"Vegetation Fractional Cover represents the exposed proportion of Photosynthetic Vegetation (PV), Non-Photosynthetic Vegetation (NPV) and Bare Soil (BS) within each pixel. The sum of the three fractions is 100% (+/- 3%) and shown in Red/Green/Blue colors. In forested canopies the photosynthetic or non-photosynthetic portions of trees may obscure those of the grass layer and/or bare soil. This product is derived from the MODIS Nadir BRDF-Adjusted Reflectance product (MCD43A4) collection 6 and has 500 meters spatial resolution. \n\nA suite of derivative products are also produced including monthly fractional cover, total vegetation cover (PV+NPV), and anomaly of total cover against the time series. \nMonthly: The monthly product is aggregated from the 8-day composites using the medoid method.\nAnomaly: represents the difference between total vegetation cover (PV+NPV) in a given month and the mean total vegetation cover for that month in all years available, expressed in units of cover. For example, if the mean vegetation cover in January (2001-current year) was 40% and the vegetation cover for the pixel in January 2018 was 30%, the anomaly for the pixel in Jan 2018 would be -10%. \nDecile: represents the ranking (in ten value intervals) for the total vegetation cover in a given month in relation to the vegetation cover in that month for all years in the time-series.\n\nMODIS fractional cover has been validated for Australia. ","keywords":"Vegetation cover, vegetation area fraction, MODIS, fractional cover, ground cover, total cover","credit":"This dataset has been developed by the Environmental Earth Observation Group, CSIRO Land and Water. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2019-11-11T15:40:22.532+11:00","leadResearcher":"Juan Guerschman","serviceCount":0,"contributors":[],"andsPid":"102.100.100/42094","doi":null,"dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:43201"},"dataCollectionId":43201,"self":"https://data.csiro.au/dap/ws/v2/collections/43201","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:43201","fileUpload":false,"fileId":0},"title":"HyLogger3 Olympic Dam","description":"Hyperspectral (VNIR/SWIR/TIR) drill core data set collected using HyLogger3 at GSSA's NVCL node at the Tonsley Core Library in Adelaide","keywords":"hyperspectral, Olympic Dam, mineralogy","credit":"Alan Mauger, GSSA NVCL Node\nTransport of drill core supported by NCRIS funds through AuScope's NVCL Infrastructure Program","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) Geological Survey of South Australia 2020.","rights":"All Rights (including copyright) Geological Survey of South Australia 2020.","published":"2020-05-01T18:04:17.942+10:00","leadResearcher":"Alan Mauger","serviceCount":0,"contributors":["Georgina Gordon","Carsten Laukamp"],"andsPid":"102.100.100/342616","doi":"10.25919/5eaadae091d8f","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:44783"},"dataCollectionId":44783,"self":"https://data.csiro.au/dap/ws/v2/collections/44783","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:44783","fileUpload":false,"fileId":0},"title":"Rocklea Dome C3DMM","description":"The Rocklea Dome 3D Mineral Mapping project was conducted by the Western Australian Centre of Excellence for 3D Mineral Mapping from 2009 to 2012 to showcase the opportunities offered by existing hyperspectral remote and proximal sensing technologies for comprehensive minerals systems analyses.\n\nKey achievements of the Rocklea Dome 3D Mineral Mapping project are (Haest et al., 2012 a,b; 2013):\n•Quantification of iron oxide phases and associated mineralogy derived from hyperspectral data and validated using X-ray diffractometry and geochemistry:•iron (oxyhydr-)oxide content: RMSE of 9.1 wt % Fe\n•Al clay content: RMSE 3.9 wt % Al2O3\n•hematite/goethite ratio: RMSE 9.0 wt % goethite\n•Spatial characterisation of vitreous vs. ochreus goethite\n•Defining the Tertiary channel boundary using key mineralogical parameters, such as the kaolin crystallinity\n•Modelling the iron ore resource of the Rocklea Dome CID\n•Identification of drill holes that were sunk into barren (i.e. bedrock) lithologies, suggesting that about a third of drill holes could have been saved\n•Detailed characterisation of clay mineralogy that is associated with distinct domains of the CID and its cover (i.e. kaolin group vs. Al-smectites vs. Fe-smectites)\n•Characterisation of mineral assemblages in the Quaternary cover of the Tertiary channel (e.g. calcrete)\n•Improvement of quality of mineral maps by application of vegetation unmixing methods\n\n\nAll of the above points showcase how hyperspectral data can be used for the whole of mine life cycle, from exploration to resource characterisation.\n","keywords":"hyperspectral, HyLogging, remote sensing, earth observation, exploration, regolith","credit":"The Rocklea Dome 3D Mineral Mapping project was funded by the Western Australian Government through their support to the Western Australian Centre of Excellence for three-dimensional mineral mapping (C3DMM) in Kensington and by Murchison Metals Ltd. M. Verrall helped with acquisition of the XRD spectra and his introduction to QXRD is greatly appreciated. M. Cardy, A. Hackett, and S. Travaglione are acknowledged for the acquisition of the infrared spectroscopic data and the preparation of samples for XRD analysis. This work profited from fruitful discussions with CSIRO colleagues C. Ong, A. Rodger, E. Ramanaidou, and M. Wells and with Murchison Metals Ltd. geologists J. Johnson and S. Peterson. The Geological Survey of Western Australia covered part of the costs for the diamond drilling through their Exploration Incentive Scheme co-funded Exploration Drilling program. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2020-06-04T10:26:06.915+10:00","leadResearcher":"Carsten Laukamp","serviceCount":0,"contributors":[],"andsPid":"102.100.100/349349","doi":"10.25919/5ed83bf55be6a","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:45994"},"dataCollectionId":45994,"self":"https://data.csiro.au/dap/ws/v2/collections/45994","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:45994","fileUpload":false,"fileId":0},"title":"RDF representation of ASLS Landform classification","description":"Machine-readable representation of the classifiers described in chapter 5 Landform, by J.G. Speight, in Australian soil and land survey field handbook (3rd edn).\n\nIn this technique for describing landforms, the whole land surface is viewed as a mosaic of tiles of odd shapes and sizes. The scheme is intended to produce a record of observations rather than inferences.","keywords":"landform; classification; SKOS; RDF; linked data; web","credit":"The data was converted from the print representation to this linked-data form by Linda Gregory assisted by Simon J D Cox.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2020-08-24T08:52:29.485+10:00","leadResearcher":"Simon Cox","serviceCount":0,"contributors":["Linda Gregory"],"andsPid":"102.100.100/368506","doi":"10.25919/5f42f2e94119c","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:45995"},"dataCollectionId":45995,"self":"https://data.csiro.au/dap/ws/v2/collections/45995","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:45995","fileUpload":false,"fileId":0},"title":"RDF representation of ASLS soil profile classification","description":"Machine-readable representation of the classifiers described in chapter 8 Soil Profile, by R.C. McDonald and R.F. Isbell, in Australian soil and land survey field handbook (3rd edn).\n\nA soil profile is a vertical section of a soil from the soil surface through all its horizons to parent material, other consolidated substrate material or selected depth in unconsolidated material.","keywords":"soil; soil profile; classification; SKOS; RDF; linked data; web","credit":"The data was converted from the print representation to this linked-data form by Linda Gregory assisted by Simon J D Cox.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2020-08-24T08:53:17.796+10:00","leadResearcher":"Simon Cox","serviceCount":0,"contributors":["Linda Gregory"],"andsPid":"102.100.100/368508","doi":"10.25919/5f42f324b2ef8","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:46108"},"dataCollectionId":46108,"self":"https://data.csiro.au/dap/ws/v2/collections/46108","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:46108","fileUpload":false,"fileId":0},"title":"Biogeochemical surveys in eastern Gulf of Carpentaria estuaries, June 2018","description":"Archive of biogeochemical data from case study and research cruise in seven estuaries of the eastern Gulf of Carpentaria. Data were collected via two observational methods:\n1) 24-36hr time series of hourly discrete samples and water-column profiles\n2) Spatial surveys at approximately low tide, which include discrete samples and water-column profiles collected along the river-ocean axis of estuaries. A small number of discrete samples of porewater were also collected from bore holes to approximately 2m depth.\nDatasets include carbon, nutrients, sediment particle size, metals, phytoplankton photopigments, CDOM (chromophoric dissolved organic matter), and vertical profiles of salinity, temperature, dissolved oxygen, pH, turbidity chlorophyll a fluorescence, and fluorescent dissolved organic matter (fDOM). \n","keywords":"Biogeochemistry; carbon; nutrients; sediments; water quality; particle size; metals; phytoplankton photopigments","credit":"Joseph R. Crosswell; Geoffrey Carlin; Daniel Gorman; Dion Frampton; James McLaughlin; Cassie Schwanger; Sarah Stephenson; Andy Steven; David Beale; Lesley Clementson; Bozena Wojtasiewicz","licence":"CSIRO Data Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1061","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2020-08-24T20:55:00.250+10:00","leadResearcher":"Joey Crosswell","serviceCount":0,"contributors":["Geoff Carlin","Daniel Gorman","Dion Frampton","James McLaughlin","Cassie Schwanger","Sarah Stephenson","Andy Steven","David Beale","Lesley Clementson","Bozena Wojtasiewicz"],"andsPid":"102.100.100/368593","doi":"10.25919/5f439be5e60a0","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:5144"},"dataCollectionId":46133,"self":"https://data.csiro.au/dap/ws/v2/collections/46133","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:5144","fileUpload":false,"fileId":0},"title":"Topographic Position Index derived from 1" SRTM DEM-S","description":"Topographic Position Index (TPI) is a topographic position classification identifying upper, middle and lower parts of the landscape. This dataset includes a mask that identifies where topographic position cannot be reliably derived in low relief areas.\n\nThe TPI product was derived from Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. A masked version of the TPI product was derived using the slope relief classification product.\n\nThe TPI data are available at 1 arc-second and 3 arc-second resolution.\n\nThe 3 arc-second resolution dataset was generated from the 1 arc-second TPI product and masked by the 3” water and ocean mask datasets.\n","keywords":"Topographic Position Index; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2012.","rights":"All Rights (including copyright) CSIRO 2012.","published":"2020-08-25T14:46:55.744+10:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin"],"andsPid":"102.100.100/8339","doi":"10.4225/08/5758CCC862AD5","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:46886"},"dataCollectionId":46886,"self":"https://data.csiro.au/dap/ws/v2/collections/46886","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:46886","fileUpload":false,"fileId":0},"title":"pyela python package for Exploratory Lithology Analysis - 0.6.5","description":"Python software for Exploratory Lithology Analysis \n\nThis package combines features to:\n\n* perform natural language processing on lithology descriptions in the logs, to detect primary and secondary lithologies\n* apply supervised machine learning to interpolate lithologies across a 3D grid\n* visualise interactively the 3D data\n","keywords":"geology; lithology; 3d-models; data-mining; facies-classification ","credit":"Juan Castilla-Rho: Initial python notebook \nJean-Michel Perraud: reengineer to a Python package, feature improvements; technical and user documentation.\n\nThe software was designed in part using a case study under the auspices of the Peel Integrated Water Initiative (PIWI), which contributes to the Transforming Peel Program, funded by the Royalties for Region Program. The project was undertaken in collaboration with the WA Department of Water and Environmental Regulation (DWER), co-funded by DWER and CSIRO. \n\n","licence":"CSIRO Open Source Software Licence (Based on MIT/BSD Open Source Licence)","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1101","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2020-10-22T16:03:35.424+11:00","leadResearcher":"Jean-Michel Perraud","serviceCount":0,"contributors":["Juan Castilla"],"andsPid":"102.100.100/384422","doi":null,"dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18491"},"dataCollectionId":48087,"self":"https://data.csiro.au/dap/ws/v2/collections/48087","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18491","fileUpload":false,"fileId":0},"title":"Mean monthly incoming atmospheric longwave radiation modelled using the 1" DEM-S - 1" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9632 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18492","keywords":"Monthly incoming longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T11:29:24.059+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39916","doi":"10.4225/08/5788852154FC9","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18492"},"dataCollectionId":48089,"self":"https://data.csiro.au/dap/ws/v2/collections/48089","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18492","fileUpload":false,"fileId":0},"title":"Mean monthly incoming atmospheric longwave radiation modelled using the 1" DEM-S - 3" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 3 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. \n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9632 . The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18491","keywords":"Monthly incoming longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T11:42:22.787+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39915","doi":"10.4225/08/578884AA56FA2","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18611"},"dataCollectionId":48090,"self":"https://data.csiro.au/dap/ws/v2/collections/48090","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18611","fileUpload":false,"fileId":0},"title":"Mean monthly net longwave radiation modelled using the 1" DEM-S - 1" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9633 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18612","keywords":"Monthly net longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T14:54:23.163+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39922","doi":"10.4225/08/57900F36C5113","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18612"},"dataCollectionId":48091,"self":"https://data.csiro.au/dap/ws/v2/collections/48091","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18612","fileUpload":false,"fileId":0},"title":"Mean monthly net longwave radiation modelled using the 1" DEM-S - 3" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 3 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. \n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9633 . The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18611 ","keywords":"Monthly net longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T12:18:20.140+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39918","doi":"10.4225/08/578D8D40AC0A2","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18670"},"dataCollectionId":48093,"self":"https://data.csiro.au/dap/ws/v2/collections/48093","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18670","fileUpload":false,"fileId":0},"title":"Mean monthly net radiation modelled using the 1" DEM-S - 1" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9630 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18671","keywords":"Monthly net radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T16:31:19.864+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39955","doi":"10.4225/08/57980D45BC556","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18671"},"dataCollectionId":48094,"self":"https://data.csiro.au/dap/ws/v2/collections/48094","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18671","fileUpload":false,"fileId":0},"title":"Mean monthly net radiation modelled using the 1" DEM-S - 3" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 3 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format.\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9630 . The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18670","keywords":"Monthly net radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T16:32:18.662+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39954","doi":"10.4225/08/579802C242E01","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9634"},"dataCollectionId":48095,"self":"https://data.csiro.au/dap/ws/v2/collections/48095","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9634","fileUpload":false,"fileId":0},"title":"Mean monthly outgoing surface longwave radiation modelled using the 1" DEM-S - 1" mosaic data","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format.\n\nThe 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18335 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18336\n","keywords":"Monthly outgoing longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T16:34:17.983+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/14041","doi":"10.4225/08/577DC332AA649","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18336"},"dataCollectionId":48096,"self":"https://data.csiro.au/dap/ws/v2/collections/48096","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18336","fileUpload":false,"fileId":0},"title":"Mean monthly outgoing surface longwave radiation modelled using the 1" DEM-S - 3" mosaic data","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe data in this collection are available at 3 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format.\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18335 . The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9634","keywords":"Monthly outgoing longwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T16:51:21.210+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39412","doi":"10.4225/08/577B02E8CF646","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18732"},"dataCollectionId":48098,"self":"https://data.csiro.au/dap/ws/v2/collections/48098","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18732","fileUpload":false,"fileId":0},"title":"Mean monthly shortwave radiation ratio modelled using the 1" DEM-S - 3" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 3 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format.\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9631 . The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18731","keywords":"Monthly shortwave radiation ratio; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T16:48:19.754+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39959","doi":"10.4225/08/5799819AE0D1C","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18852"},"dataCollectionId":48099,"self":"https://data.csiro.au/dap/ws/v2/collections/48099","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18852","fileUpload":false,"fileId":0},"title":"Mean monthly total shortwave radiation on a sloping surface modelled using the 1" DEM-S - 3" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 3 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format.\n\nThe 3 arc-second resolution versions of these radiation surfaces have been produced from the 1 arc-second resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9530 . The 1 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18851","keywords":"Monthly shortwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T17:08:19.486+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39969","doi":"10.4225/08/57A922559BDA3","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9635"},"dataCollectionId":48100,"self":"https://data.csiro.au/dap/ws/v2/collections/48100","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9635","fileUpload":false,"fileId":0},"title":"SRAD sky view factor modelled using the 1" DEM-S","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe data in this collection are available at 1 arcsecond resolution as 1x1 degree tiles (ESRI grid format) or as a single grid mosaic of Australia (TIFF format), and at 3 arcsecond resolution as a single grid of Australia (TIFF format).","keywords":"Sky view factor; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2020-12-18T17:46:59.103+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/14038","doi":"10.4225/08/579965DB0FFD9","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18731"},"dataCollectionId":48467,"self":"https://data.csiro.au/dap/ws/v2/collections/48467","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18731","fileUpload":false,"fileId":0},"title":"Mean monthly shortwave radiation ratio modelled using the 1" DEM-S - 1" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9631 .\n\nThe 3 arcsecond resolution versions of these radiation surfaces have been produced from the 1 arcsecond resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18732","keywords":"Monthly shortwave radiation ratio; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2021-01-12T11:32:19.302+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39962","doi":"10.4225/08/5799D4A672AFF","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:18851"},"dataCollectionId":48468,"self":"https://data.csiro.au/dap/ws/v2/collections/48468","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:18851","fileUpload":false,"fileId":0},"title":"Mean monthly total shortwave radiation on a sloping surface modelled using the 1" DEM-S - 1" mosaic","description":"Mean monthly solar radiation was modelled across Australia using topography from the 1 arcsecond resolution SRTM-derived DEM-S and climatic and land surface data. The SRAD model (Wilson and Gallant, 2000) was used to derive:\n•\tIncoming short-wave radiation on a sloping surface\n•\tShort-wave radiation ratio (shortwave on sloping surface / shortwave on horizontal surface)\n•\tIncoming long-wave radiation\n•\tOutgoing long-wave radiation\n•\tNet long-wave radiation\n•\tNet radiation\n•\tSky view factor\nAll radiation values are in MJ/m2/day except for short-wave radiation ratio which has no units. The sky view factor is the fraction of the sky visible from a grid cell relative to a horizontal plane.\n\nThe radiation values are determined for the middle day of each month (14th or 15th) using long-term average atmospheric conditions (such as cloudiness and atmospheric transmittance) and surface conditions (albedo and vegetation cover). They include the effect of terrain slope, aspect and shadowing (for sun positions at 5 minute intervals from sunrise to sunset), direct and diffuse radiation and sky view.\n\nThe monthly data in this collection are available at 1 arcsecond resolution as single (mosaicked) grids for Australia in TIFF format. The 1 arcsecond tiled data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:9530 .\n\nThe 3 arc-second resolution versions of these radiation surfaces have been produced from the 1 arc-second resolution surfaces, by aggregating the cells in a 3x3 window and taking the mean value.\n\nThe 3 arcsecond mosaic data can be found here: https://data.csiro.au/dap/landingpage?pid=csiro:18852","keywords":"Monthly shortwave radiation; LAND Topography Models; ECOLOGY Landscape; TERN_Soils; Land Surface;Australia","credit":"Access to this data has been made possible by the Terrestrial Ecosystem Research Network (TERN), supported by the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2021-01-12T11:34:25.348+11:00","leadResearcher":"John Gallant","serviceCount":0,"contributors":["Jenet Austin","Tom Van Niel"],"andsPid":"102.100.100/39968","doi":"10.4225/08/57A922559C76A","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:40340"},"dataCollectionId":51944,"self":"https://data.csiro.au/dap/ws/v2/collections/51944","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:40340","fileUpload":false,"fileId":0},"title":"Atlas of Australian Soils (digital)","description":"The Atlas of Australian Soils (Northcote et al, 1960-68) was compiled by CSIRO in the 1960's to provide a consistent national description of Australia's soils. It comprises a series of ten maps and associated explanatory notes, compiled by K.H. Northcote and others. The maps are published at a scale of 1:2,000,000, but the original compilation was at scales from 1:250,000 to 1:500,000.\n\nMapped units in the Atlas are soil landscapes, usually comprising a number of soil types. The explanatory notes include descriptions of soils landscapes and component soils. Soil classification for the Atlas is based on the Factual Key.\n\nThe Factual Key (Northcote 1979) was the most widely used soil classification scheme prior to the Australian Soil Classification (Isbell 2002). It dates from 1960 and was essentially based on a set of about 500 profiles largely from south-eastern Australia. It is an hierarchical scheme with 5 levels, the most detailed of which is the principal profile form (PPF). Most of the keying attributes are physical soil characteristics, and can be determined in the field.\n\nA number of map unit interpretations have been developed to assist with national perspectives on soil information. They are also available for download.\n\n1. Interpretations of soil properties based on the dominant Northcote classification (1992): The first set of interpretations of soil properties for the dominant soil of each landscape. Soil permeability, water holding capacity, texture, reaction trend, nutrient response and depth characteristics are assigned to relative classes. Report and many caveats are included.\n\n2. Australian Soil Classification conversion (1996): A table that converts the Atlas of Australian Soils mapping units to an Australian Soil Classification soil Order was compiled to aid the production of Concepts and rationale of the Australian Soil Classification. Caveats and colours included.\n\n3. Estimations of soil properties based on the dominant Northcote classification: McKenzie et al (2000) compiled tables estimating typical ranges for soil properties associated with each principal profile form (PPF) of the Factual Key. These tables were intended for use with the Atlas of Australian Soils, to provide estimates of specific soil properties for each map-unit.\n\nInterpretations for each soil type were based on the range observed in approximately 7000 soil profiles held within the CSIRO National Soil Database, with ancillary data from Northcote et al. (1975). The systematic structure of the Factual Key makes interpolation between soil classes relatively straightforward. Soil properties were estimated using a simple two-layer model of the soil consisting of an A and B horizon. The following properties have been estimated for both the A and B horizon: horizon thickness, texture, clay content, bulk density, grade of pedality and saturated hydraulic conductivity. The estimates of thickness, texture, bulk density and pedality have been used to estimate parameters that describe the soil water retention curve - these allow calculation of the available water capacity for each layer. Interpretations relating to the complete soil profile are presence or absence of calcrete and gross nutrient status.\n\nCaveats on the use of these interpretative tables to predict soil properties spatially are discussed by McKenzie et al (2000). A very large proportion of soil variation within a region occurs over short distances and cannot be resolved by reconnaissance scale maps. The qualitative nature of the Atlas and restrictions associated with the classification scheme and structure of the soil-landscape model impose further constraints. Technical reported included.\n\n","keywords":"Soil Australia Northcote Atlas","credit":"CSIRO, NRIC, Bureau of Rural Sciences (BRS)","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO, National Resource Information Centre, BRS 1991.","rights":"All Rights (including copyright) CSIRO, National Resource Information Centre, BRS 1991.","published":"2021-08-03T15:39:42.218+10:00","leadResearcher":"CSIRO","serviceCount":0,"contributors":["National Resource Information Centre, BRS"],"andsPid":"102.100.100/264762","doi":"10.25919/5f1632a855c17","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:11413"},"dataCollectionId":56856,"self":"https://data.csiro.au/dap/ws/v2/collections/56856","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:11413","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Soil Depth (3" resolution) - Release 1","description":"This is Version 1 of the Soil Depth product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. This depth product estimates the depth of soil down to 2 metres. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThe soil attribute products are provided as continuous maps that represent each of six depth intervals to a maximum depth of 2 metres. We acknowledge that soil depth is variable across Australia, and in some landscapes there might be no soil or soil might be shallower than 2 metres. We have provided continuous maps because of the relative unavailability of data on soil depth. Further, existing data on depth is biased to near surface layers and there are few records that extend beyond 1.5m. Therefore, we provide here, our best estimate of soil depth to allow users to generate masks, which might be used together with the attribute maps to approximate the presence of areas with no soil or areas with shallow soil. We encourage users to draw on local data and expertise for such assessments.\n\nAttribute Definition: Depth of soil profile (A & B horizons); \nUnits: metres; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 3; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Soil Depth; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"Development of and access to the data has been made possible by CSIRO, and the Terrestrial Ecosystem Research Network (TERN), with support from the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, and with agreement from the custodians of the soil site data of each state and territory.\nAll of the organisations listed as collaborating agencies have contributed significantly to the project and the final products.\n","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2022-11-11T09:53:36.262+11:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd"],"andsPid":"102.100.100/19205","doi":"10.4225/08/546F540FE10AA","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10877"},"dataCollectionId":56955,"self":"https://data.csiro.au/dap/ws/v2/collections/56955","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10877","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid Digital Soil Property Maps for Tasmania (3" resolution)","description":"These are the soil attribute products of the Tasmanian Soil Attribute Grids. There are 8 soil attribute products available from the TERN Soil Facility. Each soil attribute product is a collection of 6 depth slices. Each depth raster has an upper and lower uncertainty limit raster associated with it. The depths provided are 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm & 100-200cm, consistent with the Specifications of the GlobalSoilMap.\n\nAttributes: pH - Water (pHw); Electical Conductivity dS/m (ECD); Clay % (CLY); Sand % (SND); Silt % (SLT); Bulk Density - Whole Earth Mg/m3 (BDw); Organic Carbon % (SOC); Coarse Fragments >2mm (CFG).\n\nThese products were developed using datasets held by the Tasmanian Department of Primary Industries Parks Water & Environment (DPIPWE) Soils Database. The mapping was made by using spatial modelling and digital soil mapping (DSM) techniques to produce a fine resolution 3 arc-second grid of soil attribute values and their uncertainties, across all of Tasmania.\n\nNote: Previous versions of this collection contained a Depth layer. This has been removed as the units do not comply with Global Soil Map specifications.","keywords":"TERN_Soils; Soil; TERN; Raster; Attributes; Tasmania; DSM; Global Soil Map; spatial modelling; 3-dimensional soil mapping; spatial uncertainty; Bulk Density; Bulk Density - Whole Earth; Clay; Coarse Fragments; Electrical Conductivity; Organic Carbon; pH - Water; Sand; Silt; BD; EC; pH; SLGA","credit":"DPIPWE, CSIRO Land & Water, ACLEP (Australian Collaborative Land Evaluation Program), University of Sydney.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO, Tasmania Department Primary Industries, Parks, Water and Environment 2014.","rights":"All Rights (including copyright) CSIRO, Tasmania Department Primary Industries, Parks, Water and Environment 2014.","published":"2022-11-24T10:21:32.712+11:00","leadResearcher":"Darren Kidd","serviceCount":0,"contributors":["Mathew Webb","Brendan Malone","Budiman Minasny","Alex McBratney"],"andsPid":"102.100.100/16128","doi":"10.4225/08/5aaf364c54cc8","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:57406"},"dataCollectionId":57406,"self":"https://data.csiro.au/dap/ws/v2/collections/57406","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:57406","fileUpload":false,"fileId":0},"title":"TERN Soil Data Federator","description":"The SoilDataFederator is a web API that brings together soil site data from a range of disparate data sources. It removes the complexity and hassles associated with trying to access and use soil data from different sources. It allows the user to query soil data stores across Australia in a consistent manner and the data returned is a consistent format. Users do not need to know the details of each of the individual data stores structures and querying mechanisms. The data in the system is historical soil survey data and is composed of both soil morphological description data and laboratory analysis data. The SoilDataFederator will return all available data for a specified soil property.\n\nThe SoilDataFederator is a web application programming Interface (API) implemented in the R programming language. Being implemented as an API, you can use your programming language of choice to access soil data via the API. Details about using the API are available and code examples in the R language can be downloaded. There is a SwaggerUI available to let you explore the syntax of the API. The API accesses datasets that are already publicly available. The API is used to query data over the internet via a standardised set of URLs with standardised parameters. Data can be returned in a range of formats but always in a standard form optimised for delivering data on a per attribute basis. The SoilDataFederator consists of a catalogue of available datasets and a series of associated “backend” modules which query the individual data systems and transform the data on the fly to the standard form. The code base is publicly available with the idea that the soil community will develop it further in the future .","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Continental;DSM;Spatial modelling;Digital Soil Mapping;SLGA;Soil Site Data","credit":"The organisations listed in the collaborators section of this record have made soil data available through the TERN SoilDataFederator","licence":"GNU General Public Licence v3.0","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1244","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2022-12-15T10:33:12.676+11:00","leadResearcher":"Ross Searle","serviceCount":0,"contributors":[],"andsPid":"102.100.100/480151","doi":null,"dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:57382"},"dataCollectionId":57424,"self":"https://data.csiro.au/dap/ws/v2/collections/57424","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:57382","fileUpload":false,"fileId":0},"title":"TERN Digital Soil Mapping Raster Covariate Stacks","description":"There are over 150 national GeoTIFF rasters representing the SCORPAN factors across climate, parent material, biology, relief, soil and location.\n\nCovariate rasters (stored as Cloud Optimised GeoTIFF files) are available as full national mosaics. The mosaics are available at 90m (3 arcsec) resolution and at 30m (1 arcsec) resolution. \n\nGeneral information about this data set can be found at - https://aussoilsdsm.esoil.io/dsm-covariates/covariate-data\n\nThe covariates are also available as Principal Components (PCA). Details of the PCA can be found at - https://aussoilsdsm.esoil.io/dsm-covariates/covariate-data-pca\n\nThese DSM covariate datasets are available for download at the TERN Landscape File Download Site - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/GetData-COGSDataStore.html\n\nA detailed metadata listing for the covariate data is available at - https://shiny.esoil.io/Apps/Covariates/ \n\n","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Covariate;Continental;DSM;Spatial modelling;Digital Soil Mapping;SLGA","credit":"We acknowledge the original producers of these publicly available data sets. See metadata for details - - https://shiny.esoil.io/Apps/Covariates/","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2022-12-22T08:00:13.898+11:00","leadResearcher":"Ross Searle","serviceCount":0,"contributors":["Brendan Malone","John Wilford","Jenet Austin","Chris Ware","Mathew Webb","Mercedes Roman Dobarco","Tom Van Niel"],"andsPid":"102.100.100/480150","doi":"10.25919/jr32-yq58","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:57430"},"dataCollectionId":57430,"self":"https://data.csiro.au/dap/ws/v2/collections/57430","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:57430","fileUpload":false,"fileId":0},"title":"CSIRO Sentinel-1 SAR image dataset of oil- and non-oil features for machine learning ( Deep Learning )","description":"What this collection is:\nA curated, binary-classified image dataset of grayscale (1 band) 400 x 400-pixel size, or image chips, in a JPEG format extracted from processed Sentinel-1 Synthetic Aperture Radar (SAR) satellite scenes acquired over various regions of the world, and featuring clear open ocean chips, look-alikes (wind or biogenic features) and oil slick chips.\n\nThis binary dataset contains chips labelled as:\n- \"0\" for chips not containing any oil features (look-alikes or clean seas) \n- \"1\" for those containing oil features. \n\nThis binary dataset is imbalanced, and biased towards \"0\" labelled chips (i.e., no oil features), which correspond to 66% of the dataset.\nChips containing oil features, labelled \"1\", correspond to 34% of the dataset.\n\nWhy:\nThis dataset can be used for training, validation and/or testing of machine learning, including deep learning, algorithms for the detection of oil features in SAR imagery. Directly applicable for algorithm development for the European Space Agency Sentinel-1 SAR mission (https://sentinel.esa.int/web/sentinel/missions/sentinel-1 ), it may be suitable for the development of detection algorithms for other SAR satellite sensors.\n\nOverview of this dataset:\nTotal number of chips (both classes) is N=5,630\nClass \t 0\t 1\nTotal\t\t3,725\t1,905\n\nFurther information and description is found in the ReadMe file provided (ReadMe_Sentinel1_SAR_OilNoOil_20221215.txt)","keywords":"Sentinel-1; synthetic aperture radar; SAR ; artificial intelligence; AI; machine learning; ML; deep learning; DL; great barrier reef; GBR; singapore; oil slick; oil spill; oil discharge","credit":"David Blondeau-Patissier (CSIRO); Thomas Schroeder (CSIRO); Foivos Diakogiannis (CSIRO); Zhibin Li (CSIRO)","licence":"Creative Commons Attribution-ShareAlike 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1122","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2022-12-15T17:10:13.853+11:00","leadResearcher":"David Blondeau-Patissier","serviceCount":0,"contributors":["Thomas Schroeder","Foivos Diakogiannis","Zhibin Li"],"andsPid":"102.100.100/480163","doi":"10.25919/4v55-dn16","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:55799"},"dataCollectionId":57591,"self":"https://data.csiro.au/dap/ws/v2/collections/57591","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:55799","fileUpload":false,"fileId":0},"title":"FNQ_2021_V01 Voyage dataset: Feb - March 2021; Biogeochemical and hydrodynamic observations along the river-reef continuum of estuaries in eastern Cape York, Australia","description":"Archive of biogeochemical and hydrodynamic data from 2021 research voyage in eastern Cape York.\nData were collected via several observational methods including an underway, flow-though sampling system, underway CTD casts, benthic lander deployments, >25hr station keeping, water column profiling, across-axis hydrodynamic transects and along-axis profiling transects. A detailed description of data, methods, and activities is included in this archive as a voyage sampling report.","keywords":"Biogeochemistry; hydrodynamics; carbon; nutrients; sediments; acoustics; currents; water quality; particle size","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2023-01-05T14:34:26.861+11:00","leadResearcher":"Joey Crosswell","serviceCount":0,"contributors":["Geoff Carlin","Livsey Daniel","Katie Hillyer","Andy Steven"],"andsPid":"102.100.100/443950","doi":"10.25919/2vbh-cx08","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:55829"},"dataCollectionId":58215,"self":"https://data.csiro.au/dap/ws/v2/collections/58215","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:55829","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Organic Carbon (3" resolution) - Release 2","description":"This is Version 2 of the Australian Soil Organic Carbon product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of total organic carbon in soils across Australia.\n\nIt supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/547523BB0801A\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Mass fraction of carbon by weight in the < 2 mm soil material as determined by dry combustion at 900 Celcius\nUnits: %;\nPeriod (temporal coverage; approximately): 1970-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attribute; Organic Carbon; Continental; DSM; Global Soil Map; Spatial modelling;3-dimensional soil mapping; Spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO, The University of Sydney 2022.","rights":"All Rights (including copyright) CSIRO, The University of Sydney 2022.","published":"2024-08-28T16:03:51.613+10:00","leadResearcher":"Alexandre Wadoux","serviceCount":0,"contributors":["Mercedes Roman Dobarco","Brendan Malone","Budiman Minasny","Alex McBratney","Ross Searle"],"andsPid":"102.100.100/444883","doi":"10.25919/ejhm-c070","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56260"},"dataCollectionId":59206,"self":"https://data.csiro.au/dap/ws/v2/collections/59206","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56260","fileUpload":false,"fileId":0},"title":"TERN Surveillance monitoring program: Soil vis-NIR spectral library with accompanying soil measurement data for 367 specimens","description":"AusPlots is the core program delivered by TERN Surveillance. AusPlots is a plot-based surveillance monitoring program, undertaking baseline assessments of ecosystems across the country. The aim of AusPlots is to establish and maintain a national network of plots that enables consistent ecological assessment and ongoing monitoring. The AusPlots network collects a range of field data for integration with other existing data sources and current knowledge. More information about TERN Surveillance can be found at their website - https://www.tern.org.au/tern-observatory/tern-ecosystem-surveillance/\n\nAs of 2020 there are about 690 active AusPlot sites distributed across Australia.\n\nDuring 2018 to 2019, most of the soil specimens collected at the AusPlots sites were scanned with an ASD portable vis-NIR spectrometer (PANalytical Inc., Boulder, CO, USA). As there is a specific field data collection protocol carried out at each site i.e., numerous spatial distributed samples collected in a grid-design of specified dimensions, this meant a substantial number of specimens to scan. In total there were 19,380 vis-nir spectra collected. The scanning was done at CSIRO Waite Campus with a CSIRO owned vis-NIR spectrometer.\n\nAccompanying the soil vis-NIR library is a dataset of analytical soil measurements for 367 soil specimens selected the Ausplots soil specimen archive. \n\n\n\n","keywords":"soil infrared spectroscopy; visible near infrared; soil spectral inference; chemometrics","credit":"The author acknowledges the Terrestrial Ecosystem Research Network (TERN), an Australian Government NCRIS-enabled research infrastructure project, for facilitating and supporting the collection of soil vis-NIR spectral data and associated measurement data. CSIRO Waite Campus Analytical lab is acknowledged for carrying out soil measurements which underpin this work. The efforts of AusPlots, the core program delivered by TERN Surveillance, are acknowledged. Their work of field data collection, data curation and provisioning, and soil specimen archiving are critical efforts that have allowed this soil spectral data collection to occur. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2025-03-04T16:54:48.789+11:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Uta Stockmann","Seija Tuomi","Ben Sparrow"],"andsPid":"102.100.100/446811","doi":"10.25919/0wdq-wj36","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:60678"},"dataCollectionId":60678,"self":"https://data.csiro.au/dap/ws/v2/collections/60678","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:60678","fileUpload":false,"fileId":0},"title":"NVCL Yilgarn BIFs","description":"Four hyperspectral drill core data sets (AuScope NVCL) and associated whole rock geochemistry (GSWA) from three BIF-hosted high-grade iron ore deposits in the Yilgarn Craton, Western Australia.","keywords":"hyperspectral, geochemistry, drill core, banded iron formation, Yilgarn Craton","credit":"Paul Duuring (GSWA), Lena Hancock (GSWA), Carsten Laukamp (CSIRO), Michael Wawryk (GSWA)","licence":"Creative Commons Attribution-Noncommercial 4.0 Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1181","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO, Geological Survey of Western Australia 2023.","rights":"All Rights (including copyright) CSIRO, Geological Survey of Western Australia 2023.","published":"2023-10-17T18:15:12.067+11:00","leadResearcher":"Carsten Laukamp","serviceCount":0,"contributors":["Paul Duuring"],"andsPid":"102.100.100/601405","doi":"10.25919/3p68-1f62","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:60983"},"dataCollectionId":60983,"self":"https://data.csiro.au/dap/ws/v2/collections/60983","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:60983","fileUpload":false,"fileId":0},"title":"3 arcsecond climatology for continental Australia 1976-2005: Summary variables with elevation and radiative adjustment for modelling biodiversity patterns","description":"A suite of 3 arsecond resolution climate surfaces for the Australian continent, with adjustment for the radiative effects of terrain. This collection represents a 30 year average centred on 1990 (ANUCLIM derived). Precipitation, temperature, evaporation and water balance data are presented as annual means or totals and maximum and minimum monthly values.\n\nData are provided as GeoTiffs. Spatial reference system is WGS84 geographics \n\nThe data were generated using the CSIRO 'terraformer' software. A short methods summary is provided in the file 9sClimateMethodsSummary.pdf for further information, including a nomenclature for files. \n","keywords":"average climate; 1975; 2005; 1990-centred; 30 year; minumum temperature; minumum temperature; precipitation; evaporation; radiation; seasonality; digital elevation model; ANUCLIM; Australia; TERN; biodiversity; NARCLIM","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2018.","rights":"All Rights (including copyright) CSIRO 2018.","published":"2023-11-14T12:32:48.366+11:00","leadResearcher":"Thomas Harwood","serviceCount":0,"contributors":["Darran King","Martin Nolan","John Gallant","Chris Ware","Jenet Austin","Kristen Williams"],"andsPid":"102.100.100/602022","doi":"10.25919/gayv-1e32","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:59165"},"dataCollectionId":61073,"self":"https://data.csiro.au/dap/ws/v2/collections/61073","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:59165","fileUpload":false,"fileId":0},"title":"Daily 100 m land surface temperature generated through MODIS-Landsat fusion for 12 OzFlux regions across Australia during 2013-2021","description":"This collection aims to provide land surface temperature (LST) data for benchmarking algorithmic refinements of spatiotemporal fusion approaches. It contains LST data generated through MODIS-Landsat fusion for 12 OzFlux regions across Australia during 2013-2021 (and Himawari-Landsat fusion for 3 OzFlux regions within southeast Australia during 2016-2021). The area of each region is 100 × 100 km. The spatial resolution is 100 m and the temporal frequency is daily (around 10:30 am local solar time). This collection also provides the MODIS (and Himawari) and Landsat data that were used as inputs into the fusion, as well as an independent LST collection from the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) that was employed for cross-platform comparison.\n\nSeveral important updates within this version:\n\n- Updated the site description file with climate, land cover, and monthly emissivity values for each site.\n- Updated the OzFlux LST data using a new strategy. This strategy does not consider daylight saving time and does explicitly claim the 'seconds' timestep in the TOI (Time of Interests). Compared to the strategy used in our RSE paper, this strategy is expected to better coincide with the satellite overpass time. \n- Added MOD11A1 LST and viewtime data for the Australian continent during 2013-2021, with their native resolution of 1 km. Users can just simply clip the data to their targetted study areas.\n- Added the Himawari-Landsat fusion LST data for 3 OzFlux regions within southeast Australia during 2016-2021. The data format is identical to the MODIS-Landsat fusion LST data.","keywords":"Land surface temperature; Spatiotemporal fusion; ESTARFM; Bias correction; MODIS; Landsat; ECOSTRESS; Himawari","credit":"This research was performed as part of a PhD by the first author (YY) under an academic collaboration between the Australian National University (ANU) and the Commonwealth Scientific and Industrial Research Organisation (CSIRO). This research was undertaken while supported by the ANU University Research Scholarship and an ANU-CSIRO Digital Agriculture PhD Supplementary Scholarship through the Centre for Entrepreneurial Agri-Technology (CEAT). We thank the continued support of the TERN Landscapes Observatory (https://www.tern.org.au/tern-observatory/tern-landscapes/), a sensing platform of the Terrestrial Ecosystem Research Network (TERN; https://www.tern.org.au/), which is supported and enabled by the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS). We acknowledge the resources and services provided by the National Computational Infrastructure (NCI), which is also supported by the Australian Government through NCRIS. This research was supported by resources and expertise provided by CSIRO IMT Scientific Computing.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) Australian National University, CSIRO 2023.","rights":"All Rights (including copyright) Australian National University, CSIRO 2023.","published":"2023-11-23T11:36:05.540+11:00","leadResearcher":"Yi Yu","serviceCount":0,"contributors":["Luigi Renzullo","Tim McVicar","Brendan Malone","Siyuan Tian"],"andsPid":"102.100.100/486764","doi":"10.25919/rrpg-m948","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:61137"},"dataCollectionId":61137,"self":"https://data.csiro.au/dap/ws/v2/collections/61137","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:61137","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Rock outcrop occurrence (3" resolution) - Release 1","description":"The map gives a modelled estimate (probability) of the spatial distribution of rock outcroppings across Australia. \n\nThis product was produced in the development of the updated soil thickness map of Australia details of which are published in Malone and Searle (2020; https://doi.org/10.1016/j.geoderma.2020.114579). This product is the output from Model 1 of aforementioned paper and uses the Rock Properties database provided by Geoscience Australia which gives the locations of sampled rock outcrops across Australia (http://www.ga.gov.au/scientific-topics/disciplines/geophysics/rock-properties). Filtering this dataset resulted in 14616 rock outcrop locations within areas where relief >300 m. A machine learning model was used to find relationships between observed data and associated environmental covariate data to inform the mapping of rock outcrop occurrence across Australia.\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Probability of rock outcrops\nUnits: 0-1\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 1;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;NA\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attribute; Soil Thickness; Rock outcropping; Outcrops; Rock; Geology; Continental DSM; Global Soil Map; Spatial modelling; 3-dimensional soil mapping; Machine learning; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2023-12-04T15:09:52.109+11:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Ross Searle"],"andsPid":"102.100.100/602560","doi":"10.25919/82gq-pf38","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:61522"},"dataCollectionId":61522,"self":"https://data.csiro.au/dap/ws/v2/collections/61522","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:61522","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Total Nitrogen (3" resolution) - Release 2","description":"This is Version 1 of the Australian Total Soil Nitrogen product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of total nitrogen in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). An additional measure of model reliability is through assessment of model extrapolation risk. This measure provides users a spatial depiction where model estimates are made within the domain of the observed data or not.\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Total soil nitrogen;\nUnits: % (percentage of fine soil mass);\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 24;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN; TERN_Soils_DSM; TERN_Soils; Soil; Raster; Attribute; Nitrogen; N; total soil nitrogen; soil nitrogen; Continental; DSM; Global Soil Map; Spatial modelling; 3-dimensional soil mapping; Spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA; Soil and Landscape Grid of Australia","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2023.","rights":"All Rights (including copyright) CSIRO 2023.","published":"2024-01-22T10:56:56.018+11:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Ross Searle"],"andsPid":"102.100.100/603210","doi":"10.25919/pm2n-ww12","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:61526"},"dataCollectionId":61526,"self":"https://data.csiro.au/dap/ws/v2/collections/61526","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:61526","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Total Phosphorus (3" resolution) - Release 2","description":"This is Version 2 of the Australian Total Soil Phosphorus product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of total phosphorus in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). An additional measure of model reliability is through assessment of model extrapolation risk. This measure provides users a spatial depiction where model estimates are made within the domain of the observed data or not.\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Total soil phosphorus;\nUnits: % (percentage of fine soil mass);\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 24;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN; TERN_Soils_DSM; TERN_Soils; Soil; Raster; Attribute; Nitrogen; N; total soil nitrogen; soil nitrogen; Continental; DSM; Global Soil Map; Spatial modelling; 3-dimensional soil mapping; Spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA; Soil and Landscape Grid of Australia","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2024.","rights":"All Rights (including copyright) CSIRO 2024.","published":"2024-01-29T09:46:44.691+11:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Ross Searle"],"andsPid":"102.100.100/608290","doi":"10.25919/7j78-md43","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:62139"},"dataCollectionId":62139,"self":"https://data.csiro.au/dap/ws/v2/collections/62139","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:62139","fileUpload":false,"fileId":0},"title":"Mapping Blue Carbon Mitigation Opportunity: DEM","description":"This collection is part of the Mapping Blue Carbon Mitigation Opportunity [1]. \n\nThe data housed in this collection are 10m x 10m Digital Elevation Models tiled into 100km x 100km GeoTIFFs based on the DEA Product Grid [2]. The underlying base data were GA's 2023 250m [3] and The MERIT 90m elevation data [4]. All finer scale data were obtained from National and State based agencies.\n\nThe data are consolidated by state.\n\n[1] https://research.csiro.au/coastal-carbon/\n[2] https://knowledge.dea.ga.gov.au/guides/reference/collection_3_summary_grid/\n[3] https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search#/metadata/148758\n[4] https://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/index.html\n","keywords":"bathymetry; elevation; topography; DEM","credit":"Data Analysis: Dirk Slawinski, Paul Branson, Wayne Rochester\nData Sources: Geoscience Australia, AusSeabed, Australian State Agencies, CSIRO\nFunding Partner: BHP","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2024.","rights":"All Rights (including copyright) CSIRO 2024.","published":"2024-04-23T14:11:00.121+10:00","leadResearcher":"Dirk Slawinski","serviceCount":0,"contributors":["Paul Branson","Wayne Rochester"],"andsPid":"102.100.100/634852","doi":"10.25919/pwfr-mk06","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:62186"},"dataCollectionId":62186,"self":"https://data.csiro.au/dap/ws/v2/collections/62186","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:62186","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - pH - CaCl2 (3" resolution) - Release 2","description":"This is Version 2 of the Australian soil pH (CaCl2) product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of the pH of soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nAn additional measure of model reliability is through assessment of model extrapolation risk. This measure provides users a spatial depiction where model estimates are made within the domain of the observed data or not.\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: soil pH (CaCl2)\nUnits: pH units;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 24;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attribute; pH; pH (CaCl2); Continental; DSM; Global Soil Map; Spatial modelling; 3-dimensional soil mapping; Spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA; Soil and Landscape Grid of Australia","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2021.","rights":"All Rights (including copyright) CSIRO 2021.","published":"2024-04-05T15:13:11.402+11:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Ross Searle"],"andsPid":"102.100.100/609467","doi":"10.25919/7320-hw30","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:53568"},"dataCollectionId":62958,"self":"https://data.csiro.au/dap/ws/v2/collections/62958","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:53568","fileUpload":false,"fileId":0},"title":"Evaluating 3-6 month seasonal climate forecasts for decision-making in farm case studies using APSIM","description":"This data consists of APSIM v7.10 model set ups and weather files used to simulate crop production under usual practice and in response to the 3 and/or 6 month seasonal climate forecasts at 8 different case study farms. Case studies were from individual farms in the grains (including cotton), sugarcane, and rice industries in Australia (farm managers deidentified). The model setups include any modified xml files to better represent crops and other modules). The weather files include historical records obtained from the SILO data base for the nearest weather station to the farms (modified by radiation sourced from Senaps data source), 'perfect' forecasts calculated from the historical record, and seasonal climate forecasts generated from the Access-S2 and ECMWF general circulation models.","keywords":"seasonal climate forecast; APSIM; Access-S2; ECMWF","credit":"CSIRO: Elizabeth Meier (APSIM modeller), Don Gaydon (APSIM modeller), Patrick Mitchell (project leader), Andrew Schepen (climate downscaling), case study farm managers (anonymised)","licence":"Creative Commons Attribution-Noncommercial 4.0 Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1181","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-07-08T14:32:53.350+10:00","leadResearcher":"Elizabeth Meier","serviceCount":0,"contributors":["Donald Gaydon"],"andsPid":"102.100.100/434824","doi":"10.25919/erjq-4g56","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56602"},"dataCollectionId":63352,"self":"https://data.csiro.au/dap/ws/v2/collections/63352","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56602","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Coarse Fragments (3" resolution) - Release 1","description":"This is Version 1 of the Soil Coarse Fragments product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. This product contains six digital soil attribute maps for each of three depth intervals, 0-5cm, 5-15cm, 15-30cm These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated using Digital Soil Mapping methods\n\nAttribute Definition: Soil Coarse Fragments Class Probabilities as defined in the Australian Soil and Land Survey Field Handbook\nUnits: Probability of CF class occurring; \nPeriod (temporal coverage; approximately): 1950-2022; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nFormat: Cloud Optimised GeoTIFF.\n","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Continental; Australia; DSM; Global Soil Map; spatial modelling; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA; Course Fragments Probability","credit":"We thank the University of Sydney, CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) The University of Sydney 2022.","rights":"All Rights (including copyright) The University of Sydney 2022.","published":"2024-08-28T16:16:52.177+10:00","leadResearcher":"Mercedes Roman Dobarco","serviceCount":0,"contributors":["Alexandre Wadoux","Brendan Malone","Budiman Minasny","Alex McBratney","Ross Searle"],"andsPid":"102.100.100/448262","doi":"10.25919/c583-fd02","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56603"},"dataCollectionId":63354,"self":"https://data.csiro.au/dap/ws/v2/collections/63354","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56603","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Soil Organic Carbon Fractions (3" resolution) - Release 1","description":"This is Version 1 of the Soil Organic Carbon Fractions product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. This product contains six digital soil attribute maps for each of three depth intervals, 0-5cm, 5-15cm, 15-30cm These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated using Digital Soil Mapping methods\n\nAttribute Definition: Soil Organic Carbon Fractions :- mineral-associated organic carbon (MAOC), particulate organic carbon (POC) and pyrogenic organic carbon (PyOC)\nUnits: Various; \nPeriod (temporal coverage; approximately): 1950-2022; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nFormat: Cloud Optimised GeoTIFF.\n","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Continental; Australia; DSM; Global Soil Map; spatial modelling; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA;Soil Organic Carbon Fractions","credit":"We thank the University of Sydney, CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) The University of Sydney 2022.","rights":"All Rights (including copyright) The University of Sydney 2022.","published":"2024-08-28T09:47:52.301+10:00","leadResearcher":"Mercedes Roman Dobarco","serviceCount":0,"contributors":["Alexandre Wadoux","Brendan Malone","Budiman Minasny","Alex McBratney","Ross Searle"],"andsPid":"102.100.100/448266","doi":"10.25919/hqmn-zq45","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:9989"},"dataCollectionId":63356,"self":"https://data.csiro.au/dap/ws/v2/collections/63356","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:9989","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Bulk Density - Whole Earth (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Bulk Density - Whole Earth product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: Bulk Density of the whole soil (including coarse fragments) in mass per unit volume by a method equivalent to the core method; \nUnits: g/cm3; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nVariance explained (cross-validation): 0.4%; \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF. ","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Bulk Density; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; BD; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T16:24:56.434+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd"],"andsPid":"102.100.100/16109","doi":"10.4225/08/546EE212B0048","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10890"},"dataCollectionId":63358,"self":"https://data.csiro.au/dap/ws/v2/collections/63358","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10890","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Total Phosphorus (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Total Phosphorus product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: Total phosphorus; \nUnits: %; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Total Phosphorus; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T09:44:54.427+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd"],"andsPid":"102.100.100/16120","doi":"10.4225/08/546F617719CAF","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10889"},"dataCollectionId":63359,"self":"https://data.csiro.au/dap/ws/v2/collections/63359","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10889","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Total Nitrogen (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Total Nitrogen product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: Total nitrogen; \nUnits: %; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Total Nitrogen; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T09:46:54.614+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd"],"andsPid":"102.100.100/16113","doi":"10.4225/08/546F564AE11F9","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:55739"},"dataCollectionId":63360,"self":"https://data.csiro.au/dap/ws/v2/collections/63360","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:55739","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Soil Depth (3" resolution) - Release 2","description":"This is Version 2 of the Australian Soil Depth product of the Soil and Landscape Grid of Australia.\n\nIt supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/546F540FE10AA\n\nThe map gives a modelled estimate of the spatial distribution of soil depth in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Depth of soil profile (A & B horizons)\nUnits: metres;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;Soil Depth;Continental;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2020.","rights":"All Rights (including copyright) CSIRO 2020.","published":"2024-08-28T09:58:52.573+10:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Ross Searle"],"andsPid":"102.100.100/444878","doi":"10.25919/djdn-5x77","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56612"},"dataCollectionId":63363,"self":"https://data.csiro.au/dap/ws/v2/collections/63363","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56612","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Soil Bacteria and Fungi Beta Diversity (3" resolution) - Release 1","description":"This is Version 1 of the Soil Bacteria and Fungi Beta Diversity product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. These products provide estimates of the Beta Diversity of soil fungi and bacteria. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated using Digital Soil Mapping methods\n\nAttribute Definition: Soil Bacteria and Fungi Beta Diversity\nUnits: NA; \nPeriod (temporal coverage; approximately): 1950-2022; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 6; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nFormat: Cloud Optimised GeoTIFF.\n","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Continental; Australia; DSM; spatial modelling; Soil Maps; Digital Soil Mapping; SLGA; Soil Beta Diversity","credit":"We thank the University of Sydney, CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the Biome of Australia Soil Environments (BASE) for providing the DNA sequence data which made this work possible - \n\nhttps://data.bioplatforms.com/organization/about/australian-microbiome\n\nhttps://data.bioplatforms.com/organization/australian-microbiome","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) The University of Sydney 2022.","rights":"All Rights (including copyright) The University of Sydney 2022.","published":"2024-08-28T11:13:52.595+10:00","leadResearcher":"Mercedes Roman Dobarco","serviceCount":0,"contributors":["Alexandre Wadoux","Pei Pei Xue"],"andsPid":"102.100.100/448273","doi":"10.25919/4x7n-y874","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10688"},"dataCollectionId":63364,"self":"https://data.csiro.au/dap/ws/v2/collections/63364","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10688","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Silt (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Silt product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: 2-200 μm mass fraction of the less than 2 mm soil material determined using the pipette method; \nUnits: %; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.\n","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Silt; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T11:16:53.870+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd","David Clifford"],"andsPid":"102.100.100/16112","doi":"10.4225/08/546F48D6A6D48","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56750"},"dataCollectionId":63365,"self":"https://data.csiro.au/dap/ws/v2/collections/63365","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56750","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Silt (3" resolution) - Release 2","description":"This is Version 2 of the Australian Soil Silt Content product of the Soil and Landscape Grid of Australia.\n\nIt supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/546F48D6A6D48\n\nThe map gives a modelled estimate of the spatial distribution of silt in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: 2-20 um mass fraction of the < 2 mm soil material determined using the pipette method\nUnits: %;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;Silt;Continental;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T11:18:51.961+10:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Ross Searle"],"andsPid":"102.100.100/448280","doi":"10.25919/2ew1-0w57","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:55735"},"dataCollectionId":63366,"self":"https://data.csiro.au/dap/ws/v2/collections/63366","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:55735","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Sand (3" resolution) - Release 2","description":"This is Version 2 of the Australian Soil Sand Content product of the Soil and Landscape Grid of Australia.\n\nIt supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/546F29646877E\n\nThe map gives a modelled estimate of the spatial distribution of sand in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: 20 um - 2 mm mass fraction of the < 2 mm soil material determined using the pipette method\nUnits: %;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;Sand;Continental;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T11:20:52.057+10:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Ross Searle"],"andsPid":"102.100.100/444877","doi":"10.25919/rjmy-pa10","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10149"},"dataCollectionId":63367,"self":"https://data.csiro.au/dap/ws/v2/collections/63367","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10149","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Sand (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Sand product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: 200 μm - 2 mm mass fraction of the less than 2 mm soil material determined using the pipette method; \nUnits: %; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.\n","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Sand; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T11:30:54.088+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd","David Clifford"],"andsPid":"102.100.100/16111","doi":"10.4225/08/546F29646877E","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:11030"},"dataCollectionId":63371,"self":"https://data.csiro.au/dap/ws/v2/collections/63371","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:11030","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - pH - CaCl2 (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil pH - CaCl2 product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: pH of 1:5 soil/0.01M calcium chloride extract; \nUnits: None; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.\n","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; pH - CaCl2; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T15:57:53.073+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd"],"andsPid":"102.100.100/19204","doi":"10.4225/08/546F17EC6AB6E","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56703"},"dataCollectionId":63372,"self":"https://data.csiro.au/dap/ws/v2/collections/63372","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56703","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - pH (Water) (3" resolution) - Release 1","description":"This is Version 1 of the Australian pH (Water) product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of soil pH (1:5 soil water solution) in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: pH of a 1:5 soil water solution\nUnits: None;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;pH;pH (Water);Continental;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T16:00:53.100+10:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":[],"andsPid":"102.100.100/448272","doi":"10.25919/37z2-0q10","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:11467"},"dataCollectionId":63374,"self":"https://data.csiro.au/dap/ws/v2/collections/63374","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:11467","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Organic Carbon (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Organic Carbon product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: Mass fraction of carbon by weight in the less than 2 mm soil material as determined by dry combustion at 900° C; \nUnits: %; \nPeriod (temporal coverage; approximately): 2000-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF. ","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Organic Carbon; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T16:06:59.910+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd"],"andsPid":"102.100.100/19219","doi":"10.4225/08/547523BB0801A","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56551"},"dataCollectionId":63375,"self":"https://data.csiro.au/dap/ws/v2/collections/63375","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56551","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Organic Carbon (1" resolution) - Release 1","description":"This is Version1 of the Australian Soil Organic Carbon product of the Soil and Landscape Grid of Australia at 30m resolution.\n\nThe map gives a modelled estimate of the spatial distribution of total organic carbon in soils across Australia.\n\nIt supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/547523BB0801A\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 1 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Mass fraction of carbon by weight in the < 2 mm soil material as determined by dry combustion at 900 Celcius\nUnits: %;\nPeriod (temporal coverage; approximately): 1970-2021;\nSpatial resolution: 1 arc seconds (approx 30m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attribute; Organic Carbon; Continental; DSM; Global Soil Map; Spatial modelling;3-dimensional soil mapping; Spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) The University of Sydney 2022.","rights":"All Rights (including copyright) The University of Sydney 2022.","published":"2024-08-28T16:08:51.301+10:00","leadResearcher":"Alexandre Wadoux","serviceCount":0,"contributors":["Mercedes Roman Dobarco","Brendan Malone","Budiman Minasny","Alex McBratney","Ross Searle"],"andsPid":"102.100.100/448264","doi":"10.25919/5qjv-7s27","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:11017"},"dataCollectionId":63376,"self":"https://data.csiro.au/dap/ws/v2/collections/63376","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:11017","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Effective Cation Exchange Capacity (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Effective Cation Exchange Capacity product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: Cations extracted using barium chloride (BaCl2) plus exchangeable H + Al; \nUnits: meq/100g; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.\n","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Effective Cation Exchange Capacity; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T16:11:52.841+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd"],"andsPid":"102.100.100/16130","doi":"10.4225/08/546F091C11777","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56704"},"dataCollectionId":63377,"self":"https://data.csiro.au/dap/ws/v2/collections/63377","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56704","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Drained Upper Limit Volumetric Water Content (Percent) (3 arc second resolution) Version 1","description":"This is Version 1 of the Australian Drained Upper Limit Volumetric Water Content (DUL) product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of DUL soil hydraulic property in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Drained Upper Limit Volumetric Water Content\nUnits: percent;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;Soil Hydraulic Properties;Drained Upper Limit Volumetric Water Content;Continental;DUL;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T16:13:51.510+10:00","leadResearcher":"Ross Searle","serviceCount":0,"contributors":["P.D.S.N Somarathna"],"andsPid":"102.100.100/448271","doi":"10.25919/jnvd-3a26","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:11393"},"dataCollectionId":63378,"self":"https://data.csiro.au/dap/ws/v2/collections/63378","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:11393","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Depth of Regolith (3" resolution) - Release 2","description":"This is Version 2 of the Depth of Regolith product of the Soil and Landscape Grid of Australia (produced 2015-06-01).\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nAttribute Definition: The regolith is the in situ and transported material overlying unweathered bedrock; \nUnits: metres; \nSpatial prediction method: data mining using piecewise linear regression; \nPeriod (temporal coverage; approximately): 1900-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute:3; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nVariance explained (cross-validation): R^2 = 0.38; \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Depth of Regolith; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2015.","rights":"All Rights (including copyright) CSIRO 2015.","published":"2024-08-28T16:15:52.315+10:00","leadResearcher":"John Wilford","serviceCount":0,"contributors":["Ross Searle","Mark Thomas","Mike Grundy"],"andsPid":"102.100.100/19201","doi":"10.4225/08/55C9472F05295","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:55684"},"dataCollectionId":63379,"self":"https://data.csiro.au/dap/ws/v2/collections/63379","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:55684","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Clay (3" resolution) - Release 2","description":"This is Version 2 of the Australian Soil Clay Content product of the Soil and Landscape Grid of Australia.\n\nIt supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/546EEE35164BF\n\nThe map gives a modelled estimate of the spatial distribution of clay in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: 2 μm mass fraction of the less than 2 mm soil material determined using the pipette method;\nUnits: %;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;Clay;Continental;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T16:18:51.310+10:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":["Ross Searle"],"andsPid":"102.100.100/443480","doi":"10.25919/hc4s-3130","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:10168"},"dataCollectionId":63380,"self":"https://data.csiro.au/dap/ws/v2/collections/63380","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:10168","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Clay (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Clay product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: 2 μm mass fraction of the less than 2 mm soil material determined using the pipette method; \nUnits: %; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF.\n","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Clay; Continental; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T16:19:52.571+10:00","leadResearcher":"Raphael Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd","David Clifford"],"andsPid":"102.100.100/16110","doi":"10.4225/08/546EEE35164BF","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:55865"},"dataCollectionId":63381,"self":"https://data.csiro.au/dap/ws/v2/collections/63381","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:55865","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Cation Exchange Capacity (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Cation Exchange Capacity product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of cation exchange capacity in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Cation Exchange Capacity\nUnits: meq/100g;\nPeriod (temporal coverage; approximately): 1970-2022;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attribute; Available; Cation; CEC; Cation Exchange Capacity; Continental; DSM; Global Soil Map; Spatial modelling;3-dimensional soil mapping; Spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T16:22:51.121+10:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":[],"andsPid":"102.100.100/448263","doi":"10.25919/pkva-gf85","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:59277"},"dataCollectionId":63382,"self":"https://data.csiro.au/dap/ws/v2/collections/63382","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:59277","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Bulk Density - Whole Earth - Release 2","description":"This is Version 2 of the Australian Soil Bulk Density - Whole Earth product of the Soil and Landscape Grid of Australia.\n\nIt supersedes the Release 1 product that can be found at https://doi.org/10.4225/08/546EE212B0048\n\nThe map gives a modelled estimate of the spatial distribution of Bulk Density in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Bulk Density of the whole soil (including coarse fragments) in mass per unit volume by a method equivalent to the core method;\nUnits: g/cm3;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;Bulk Density;Continental;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2023.","rights":"All Rights (including copyright) CSIRO 2023.","published":"2024-08-28T16:23:51.260+10:00","leadResearcher":"Brendan Malone","serviceCount":0,"contributors":[],"andsPid":"102.100.100/486760","doi":"10.25919/gxyn-pd07","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:11016"},"dataCollectionId":63383,"self":"https://data.csiro.au/dap/ws/v2/collections/63383","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:11016","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Available Water Capacity (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Available Water Capacity product of the Soil and Landscape Grid of Australia. \n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (http://www.globalsoilmap.net/). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). \n\nThese maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia. \n\nAttribute Definition: Available water capacity computed for each of the specified depth increments; \nUnits: %; \nPeriod (temporal coverage; approximately): 1950-2013; \nSpatial resolution: 3 arc seconds (approx 90m); \nTotal number of gridded maps for this attribute: 18; \nNumber of pixels with coverage per layer: 2007M (49200 * 40800); \nTotal size before compression: about 8GB; \nTotal size after compression: about 4GB; \nData license : Creative Commons Attribution 4.0 (CC BY); \nVariance explained (cross-validation): 0.4%; \nTarget data standard: GlobalSoilMap specifications; \nFormat: GeoTIFF. ","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attributes; Available Water Capacity; Continental; Australia; DSM; Global Soil Map; spatial modelling; visible-near infrared spectroscopy; 3-dimensional soil mapping; spatial uncertainty; Soil Maps; Digital Soil Mapping; AWC; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy and the Super Science Initiative, for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. We thank also D. Jacquier and P. Wilson for their inputs.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2014.","rights":"All Rights (including copyright) CSIRO 2014.","published":"2024-08-28T16:26:52.594+10:00","leadResearcher":"RA Viscarra Rossel","serviceCount":0,"contributors":["Charlie Chen","Mike Grundy","Ross Searle","David Clifford","Nathan Odgers","Karen Holmes","Ted Griffin","Craig Liddicoat","Darren Kidd"],"andsPid":"102.100.100/16129","doi":"10.4225/08/546ED604ADD8A","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56710"},"dataCollectionId":63384,"self":"https://data.csiro.au/dap/ws/v2/collections/63384","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56710","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Available Volumetric Water Capacity (Percent) (3 arc second resolution) Version 2","description":"This is Version 2 of the Australian Available Volumetric Water Capacity (AWC) product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of AWC soil hydraulic property in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Available Volumetric Water Capacity\nUnits: percent;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;Soil Hydraulic Properties;Available Water Capacity;Continental;DUL;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T16:27:51.237+10:00","leadResearcher":"Ross Searle","serviceCount":0,"contributors":["P.D.S.N Somarathna","Brendan Malone"],"andsPid":"102.100.100/448270","doi":"10.25919/4jwj-na34","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:55864"},"dataCollectionId":63385,"self":"https://data.csiro.au/dap/ws/v2/collections/63385","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:55864","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Available Phosphorus (3" resolution) - Release 1","description":"This is Version 1 of the Australian Available Phosphorus product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of available phosphorus in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: Available Phosphorus\nUnits: mg/kg;\nPeriod (temporal coverage; approximately): 1970-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils; TERN_Soils_DSM; Soil; TERN; Raster; Attribute; Available; Phosphorus; Continental; DSM; Global Soil Map; Spatial modelling;3-dimensional soil mapping; Spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T16:29:51.106+10:00","leadResearcher":"Peter Zund","serviceCount":0,"contributors":[],"andsPid":"102.100.100/448261","doi":"10.25919/6qzh-b979","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:56709"},"dataCollectionId":63387,"self":"https://data.csiro.au/dap/ws/v2/collections/63387","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:56709","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - 15 Bar Lower Limit Volumetric Water Content (Percent) (3 arc second resolution) Version 1","description":"This is version 1 of the Australian15 Bar Lower Limit Volumetric Water Content (L15) product of the Soil and Landscape Grid of Australia.\n\nThe map gives a modelled estimate of the spatial distribution of L15 soil hydraulic property in soils across Australia.\n\nThe Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm. These depths are consistent with the specifications of the GlobalSoilMap.net project (https://esoil.io/TERNLandscapes/Public/Pages/SLGA/Resources/GlobalSoilMap_specifications_december_2015_2.pdf). The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Definition: 15 Bar Lower Limit Volumetric Water Content\nUnits: percent;\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 18;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN_Soils;TERN_Soils_DSM;Soil;TERN;Raster;Attribute;Soil Hydraulic Properties;15 Bar; Lower Limit Volumetric Water Content;Continental;DUL;DSM;Global Soil Map;Spatial modelling;3-dimensional soil mapping;Spatial uncertainty;Soil Maps;Digital Soil Mapping;SLGA","credit":"We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy for funding the project. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2022.","rights":"All Rights (including copyright) CSIRO 2022.","published":"2024-08-28T16:34:51.393+10:00","leadResearcher":"Ross Searle","serviceCount":0,"contributors":["P.D.S.N Somarathna"],"andsPid":"102.100.100/448265","doi":"10.25919/awp8-nv68","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:64292"},"dataCollectionId":65625,"self":"https://data.csiro.au/dap/ws/v2/collections/65625","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:64292","fileUpload":false,"fileId":0},"title":"Stable carbon isotope values of plant bulk tissue from 540 species surveyed across Australia between 2011 and 2022","description":"This data set contains the stable isotope carbon values for plants surveyed by Australia’s Terrestrial Ecosystem Research Network (TERN) between 2011 and May 2022 (inclusive). This data was produced to assign a photosynthetic pathway for 540 species that had no recorded pathway. This photosynthetic pathway data set was created by TERN to enable research examining the abundance, richness, and distribution of C4 and C3 vegetation in Australia. The full details of photosynthetic pathway data can be found in the linked collection: Munroe, S., McInerney, F., Andrae, J., Welti, N., Guerin, G., Leitch, E., Hall, T., Szarvas, S., Atkins, R., Caddy-Retalic, S., Holtum, J. & Sparrow, B. (2020): The Photosynthetic Pathways of Plant Species Surveyed in TERN Ecosystem Surveillance Plots. Version 2.0. Terrestrial Ecosystem Research Network. (Dataset). https://doi.org/10.25901/k61f-yz90","keywords":"Photosynthetic pathway; stable isotope; carbon; plant characteristics; vegetation; TERN; IsotopesAU","credit":"This work was funded by the Terrestrial Ecosystem Research Network (TERN), an Australian Government NCRIS-enabled project.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) Terrestrial Ecosystem research network (TERN) 2024.","rights":"All Rights (including copyright) Terrestrial Ecosystem research network (TERN) 2024.","published":"2025-05-23T14:07:51.424+10:00","leadResearcher":"Samantha Munroe","serviceCount":0,"contributors":["Cesca McInerney","Jake Andrae","Nina Welti","Gregory Guerin","Leitch Emrys","Tony Hall","Steve Szarvas","Rachel Atkins","Stefan Caddy-Retalic","Joseph Holtum","Ben Sparrow"],"andsPid":"102.100.100/660719","doi":"10.25919/0khp-ya20","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:66148"},"dataCollectionId":66148,"self":"https://data.csiro.au/dap/ws/v2/collections/66148","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:66148","fileUpload":false,"fileId":0},"title":"Soil and Landscape Grid National Soil Attribute Maps - Soil Inorganic Carbon (3" resolution) - Release 1","description":"This is Version 1 of the Australian Soil Inorganic Carbon products of the Soil and Landscape Grid of Australia.\n\nThe creation of this dataset (national estimates of presence and absence, depth to, concentration, and stocks of soil inorganic carbon) was performed by Ng et al. (2025) and published in Geoderma that was tiled: Mapping the distribution and magnitude of soil inorganic and organic carbon stocks across Australia. The work is available at: https://doi.org/10.1016/j.geoderma.2025.117239. \n\nSoil Inorganic Carbon content are a set of six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm.\n\nClassification maps of presence and absence of carbonates are a set of six digital soil attribute maps, representing the soil attribute at six depths: 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm and 100-200cm.\n\nThere is a single classification map showing depth to carbonates.\n\nDetailed information about the Soil and Landscape Grid of Australia can be found at - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html\n\nAttribute Soil Inorganic Carbon;\nUnits: Classification maps of presence and absence of carbonates [0: absent; 1: carbonates are present]. depth_to_carbonates [0: Carbonates are absent, 1: Carbonates are present at depth of 100-200cm, 2: Carbonates are present at depth of 60-100cm, 3: Carbonates are present at depth of 30-60cm, 4: Carbonates are present at depth of 15-30cm, 5: Carbonates are present at depth of 5-15cm, 6: Carbonates are present at depth of 0-5cm]. Soil Inorganic Carbon content [%];\nPeriod (temporal coverage; approximately): 1950-2021;\nSpatial resolution: 3 arc seconds (approx 90m);\nTotal number of gridded maps for this attribute: 23;\nNumber of pixels with coverage per layer: 2007M (49200 * 40800);\nData license : Creative Commons Attribution 4.0 (CC BY);\nTarget data standard: GlobalSoilMap specifications;\nFormat: Cloud Optimised GeoTIFF;","keywords":"TERN; TERN_Soils_DSM; TERN_Soils; Soil; Raster; Attribute; inorganic carbon; Continental; DSM; Global Soil Map; Spatial modelling; 3-dimensional soil mapping; Spatial uncertainty; Soil Maps; Digital Soil Mapping; SLGA; Soil and Landscape Grid of Australia","credit":"The authors acknowledge the support of the Australian Research Council Laureate Fellowship (FL210100054) on Soil Security entitled ‘A calculable approach to securing Australia’s soil’. Minasny is supported by the Australian Research Council Discovery project “Forecasting soil conditions” (DP200102542). This research was supported by funding from the National Soil Carbon Innovation Challenge Round 2 titled “An integrated schema for soil carbon stock estimation and crediting”. The authors thank Dr John Wilford from Geoscience Australia for providing the NGSA dataset and Dr Elisabeth Bui for her comments on the draft.\n\nFor publishing this data We thank the CSIRO, Terrestrial Ecosystem Research Network (TERN), the Australian Government through the National Collaborative Research Infrastructure Strategy. We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the dataset publication and its outcomes.","licence":"Creative Commons Attribution-Noncommercial 4.0 Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1181","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) The University of Sydney 2025.","rights":"All Rights (including copyright) The University of Sydney 2025.","published":"2025-07-30T15:14:29.365+10:00","leadResearcher":"Wartini Ng","serviceCount":0,"contributors":["Jose Padarian","Mercedes Roman Dobarco","Budiman Minasny","Alex McBratney","Brendan Malone"],"andsPid":"102.100.100/707457","doi":"10.25919/z65z-4472","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:66355"},"dataCollectionId":66355,"self":"https://data.csiro.au/dap/ws/v2/collections/66355","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:66355","fileUpload":false,"fileId":0},"title":"Environmental covariates stack for biodiversity and ecosystem modelling at 90m and 250m for continental Australia","description":"These stacks of 125 environmental covariates are a subset of those compiled by TERN, with the addition of new covariates developed by TERN, Geoscience Australia and CSIRO. These data were pre-processed and standardised for use in the Habitat Condition Assessment System version 3, at 250m and 90m grid resolutions. The covariates are equally applicable to biodiversity and ecosystem modelling where the conceptual framework requires that the signature of anthropogenic land use be minimised. That is, the environmental covariates represent, as far as possible, the equilibrium state of the environment prior to industrialisation of the landscape following European colonisation of the Australian continent (c.1750). While the temporal window associated with source data used in developing many of these covariates varies, each covariate is intended to represent the long-term (multi-decadal) equilibrium state, approximating pre-1750. The careful selection of covariates that meet this conceptual framework requirement of 'non-anthropogenic' distinguishes this covariate stack from other compilations. \n\nThe 250 m dataset is published in a geographic reference system (0.0025 degrees of latitude and longitude) in GDA94 (EPSG: 4283). The 90 m dataset is published in a projected reference system (Australian Albers in GDA94; EPSG: 3577). Each dataset is published as a cloud-optimised GeoTIFF (COG) in its original units and as the z-score standardised version, for the convenience of different applications. The z-score parameters for each covariate are included in the collection. \n\nDataset names do not change, only the folder in which they are contained distinguishes the resolution and whether the data are standardised or not. \n\nEach dataset is also published with the expanded coastline and hole-filled, as described in Liu et al. (2025) to ensure all continental data pixels have a value. This ensures flexibility for other uses in making decisions about where to set the coastline. The original data compiled by TERN (Searle et al., 2022) shows where data holes were filled, as this varied between datasets. The input and output mask datasets used in developing the 250m and 90m versions of HCAS are therefore also supplied to facilitate use in different applications. \n\nAll compiled covariates are potentially relevant in a range of ecosystem and biodiversity modelling applications, including HCAS, and represent a subset of the hundreds of covariates in the original TERN compilation (Searle et al., 2022). Descriptions and citations associated with each dataset were reviewed, checked against sources, and updated for accuracy. The updated descriptions and source citations are provided for the 125 datasets included in this collection. \n\nFor method details, see Liu et al. (2025): Liu N, Williams KJ, Searle R, Wilford J, Botha E, Johnson S, Read A, Valavi R, Lehmann E, Giljohann KM and Joehnk K (2025) Environmental covariates for predicting the reference state of ecosystems in the Habitat Condition Assessment System (HCAS). Technical Report EP2025-2352. CSIRO, Canberra, Australia.","keywords":"Biodiversity; Ecosystem; Condition; Modelling; HCAS; Climate; Soils; Geology; Lithology; Landform; Terrain; Coast; inundation; snow; environment; covariate; predictors; SLGA; TERN; Geoscience Australia; Habitat Condition Assessment System; non-anthropogenic; Soil and Landscape Grid of Australia","credit":"The work presented in this document and data collection was funded by DCCEEW through the Priority Improvements to the Habitat Condition Assessment System project, by NCRIS through the Terrestrial Ecosystem Research Network (TERN) Landscapes platform, and by Geoscience Australia's rock attribute modelling initiative. \n\nThe Habitat Condition Assessment System for Australia is an ongoing partnership between Commonwealth Scientific and Industrial Research Organisation (CSIRO) and the Australian Government Department of Climate Change, Energy, the Environment and Water (DCCEEW). \n\nGeoscience Australia is acknowledged for the modelled rock oxides and conductivity products, and coastline products. Contributors to the Terrestrial Ecosystem Research Network (TERN) are acknowledged for the compilation of 90 m environmental covariates and the Soil and Landscape Grid for Australia (SLGA) collections, upon which this data collection is primarily based. \n\nCSIRO and DCCEEW acknowledge the Traditional Owners of country throughout Australia and recognise their continuing connection to land, waters and culture. We pay our respects to their Elders past and present. View CSIRO’s vision towards reconciliation and DCCEEW’s Statement of Commitment to First Nations people.\n\nWe thank James Goodwin of Geoscience Australia for providing advice about which of the alternative gravity and magnetics datasets would best suit our purpose. We thank Stephen Sagar of Geoscience Australia for advice on which datasets depicting the dynamics of Australian coastlines that would best suit our purposes. We also thank Leo Lymburner (Geoscience Australia) and Jenet Austin (CSIRO) for their advice on the development of accumulated flow.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2025.","rights":"All Rights (including copyright) CSIRO 2025.","published":"2026-01-22T21:06:37.841+11:00","leadResearcher":"Ning Liu","serviceCount":0,"contributors":["Kristen Williams","Ross Searle","John Wilford","Hannelie Botha","Steph Johnson","Arthur Read","Roozbeh Valavi","Eric Lehmann","Kate Giljohann","Klaus Joehnk"],"andsPid":"102.100.100/712641","doi":"10.25919/73vy-sc68","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:66356"},"dataCollectionId":66410,"self":"https://data.csiro.au/dap/ws/v2/collections/66410","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:66356","fileUpload":false,"fileId":0},"title":"Hydrodynamic and sediment observations in Fitzroy Estuary QLD and Cassady Creek (Hinchinbrook, QLD) 2024-2025: CSIRO Tidal Inundation project","description":"This dataset compiles field observations collected as part of CSIRO’s Tidal Inundation project, 2024-2025. The field campaign deployed oceanographic and tide level sensors in two Queensland estuaries: the Fitzroy Estuary and Cassady Creek (Hinchinbrook Shire). Additional project information, deployment details, site maps and quality control notes are provided in the data_summary pdf and time_series_summary spreadsheets. \n\nGeophysical survey data collected during this study, including multibeam sonar bathymetry and aerial LiDAR surveys, are not included in this dataset but are available in a separate data collection associated with the Tidal Inundation project (see related links below).\n\nPeriodic field trips were undertaken during the 12-month study to scout, deploy, maintain and retrieve instrumentation at several fixed stations. Instrumentation consisted of tide level sensors, acoustic doppler current profilers (ADCPs), and wave monitoring buoys with pressure and temperature sensors. Additionally, 38 discrete samples of surface sediments were collected by manual grabs to quantify grain size throughout the Fitzroy Estuary and its distributary (Casuarina Creek). \n\nThis data collection includes brief quality control reports prepared after retrieval of each ADCP, with additional QC notes included in the data summary document. Data in this repository are grouped by instrument type and location. All timestamps are in local time (GMT +10), unless otherwise noted.\n","keywords":"tides; tidal inundation; blue carbon; estuary; hydrodynamics; sediment; biogeochemistry; acoustics; currents; grain size; ADCP","licence":"Creative Commons Attribution-Noncommercial 4.0 Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1181","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2025.","rights":"All Rights (including copyright) CSIRO 2025.","published":"2025-09-01T10:31:43.361+10:00","leadResearcher":"Joey Crosswell","serviceCount":0,"contributors":["Geoff Carlin","Bryan Hally","Paul Branson","Andy Steven"],"andsPid":"102.100.100/708752","doi":"10.25919/dxx2-s727","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:66536"},"dataCollectionId":66536,"self":"https://data.csiro.au/dap/ws/v2/collections/66536","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:66536","fileUpload":false,"fileId":0},"title":"Stable isotope data from Nurioopta vineyard field experiment (2023-2025)","description":"This data presents stable isotope data collected over two growing seasons (2023-2035) in order to partition irrigation sources. Stable isotope ratios of hydrogen (H), oxygen (O) and strontium (Sr) were measured in soil, irrigation, precipitation and Vitis vinifera (grapes, canes, and leaves). ","keywords":"stable isotopes; traceability; provenance; irrigation; agriculture; viticulture; IsotopesAU","credit":"CSIRO, SARDI, PIRSA","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2025.","rights":"All Rights (including copyright) CSIRO 2025.","published":"2026-01-27T16:28:09.512+11:00","leadResearcher":"Ellyse Bunney","serviceCount":0,"contributors":["Jodie Pritchard","Cesca McInerney","Paul Petrie","Nina Welti"],"andsPid":"102.100.100/712712","doi":"10.25919/jp66-pw70","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:69294"},"dataCollectionId":69294,"self":"https://data.csiro.au/dap/ws/v2/collections/69294","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:69294","fileUpload":false,"fileId":0},"title":"Australia-wide 30 m machine learning-derived canopy height models composites: best pick and median","description":"This dataset is part of the OzTreeMap project and provides two new 30 m spatial resolution canopy height products for continental Australia: (1) the best-pick canopy height model (pick-CHM); and (2) the median canopy height model (med-CHM). Both products were generated and validated as part of the study titled “Accuracy of Machine Learning-Derived Canopy Height Models at Continental Scale.”\n\nThe pick-CHM is a composite model in which each 30 m pixel adopts the most accurate canopy height value among four publicly available machine learning-derived CHMs—Tolan et al. (2024), Lang et al. (2023), Potapov et al. (2021), and Liao et al. (2020)—based on the vegetation class (Scarth et al., 2019) that the pixel represents and our vegetation-specific accuracy assessment (see lineage). The med-CHM represents a pixel-wise median composite of the same four CHMs and achieved the highest overall accuracy when validated against 22,967 km² of reference airborne point cloud data across 16 Australian vegetation classes.\n\nBoth datasets are provided as single-band GeoTIFF rasters in EPSG:3577 (Australian Albers) coordinate reference system, with 30 m spatial resolution and float32 data type. These CHMs offer improved accuracy and spatial consistency compared to the individual global products supporting continental-scale applications in forest structure monitoring, carbon accounting, and ecosystem assessment.\n\nReferences\nLang, N., Jetz, W., Schindler, K., Wegner, J.D., 2023. A high-resolution canopy height model of the Earth. Nat Ecol Evol 7, 1778–1789. https://doi.org/10.1038/s41559-023-02206-6\n\nLiao, Z., van Dijk, A.I.J.M., He, B., Larraondo, P.R., Scarth, P.F., 2020. Woody vegetation cover, height and biomass at 25 m resolution across Australia derived from multiple site, airborne and satellite observations. Int. J. Appl. Earth Obs. Geoinf. 93, 102209. https://doi.org/10.1016/j.jag.2020.102209\n\nPotapov, P., Li, X., Hernandez-Serna, A., Tyukavina, A., Hansen, M.C., Kommareddy, A., Pickens, A., Turubanova, S., Tang, H., Silva, C.E., Armston, J., Dubayah, R., Blair, J.B., Hofton, M., 2021. Mapping global forest canopy height through integration of GEDI and Landsat data. Remote Sens. Environ. 253, 112165. https://doi.org/10.1016/j.rse.2020.112165\n\nScarth, P., Armston, J., Lucas, R., Bunting, P., 2019. A structural classification of Australian vegetation using ICESat/GLAS, ALOS PALSAR, and Landsat sensor data. Remote Sens. 11, 147. https://doi.org/10.3390/rs11020147\n\nTolan, J., Yang, H.-I., Nosarzewski, B., Couairon, G., Vo, H.V., Brandt, J., Spore, J., Majumdar, S., Haziza, D., Vamaraju, J., Moutakanni, T., Bojanowski, P., Johns, T., White, B., Tiecke, T., Couprie, C., 2024. Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar. Remote Sens. Environ. 300, 113888. https://doi.org/10.1016/j.rse.2023.113888","keywords":"satellite; continental; 30 m; monocular depth estimation; CHM","credit":"Australian National University, Commonwealth Scientific and Industrial Research Organisation (CSIRO), ELVIS - Elevation and Depth - Foundation Spatial Data (Geoscience Australia)","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1221","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) Australian National University, CSIRO 2025.","rights":"All Rights (including copyright) Australian National University, CSIRO 2025.","published":"2025-10-29T09:48:19.993+11:00","leadResearcher":"Nicolas Pucino","serviceCount":0,"contributors":["Tim McVicar","Shaun Levick","Albert van Dijk"],"andsPid":"102.100.100/710836","doi":null,"dataRestricted":"TRUE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:63771"},"dataCollectionId":69371,"self":"https://data.csiro.au/dap/ws/v2/collections/69371","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:63771","fileUpload":false,"fileId":0},"title":"Mapping Australia's Coastal Defences Structures: Understanding the Gaps and the Need for a National Dataset","description":"This dataset and accompanying RMarkdown notebook document the analysis and efforts to consolidate spatial data on coastal protection structures, such as sea walls, groynes, and wharfs, across Australia's coastline. The project addresses the urgent need for a national-level dataset by sourcing data from various state governments and identifying gaps in coverage. The dataset integrates contributions from OpenStreetMap (OSM), Smartline, and state-based government databases, resulting in a research-quality geospatial file. Key attributes include the location and type of coastal structures, with data standardised for consistency across regions. Limitations are noted, such as the absence of government-supplied data for certain regions and potential accuracy issues with OSM-sourced information. The dataset is intended for research purposes, supporting efforts to assess coastal risks and guide future protection measures. Ongoing updates to datasets will extend to not only consider engineered hard structures but also include datasets of nature-based coastal protection (e.g., restored reefs and coastal vegetation).","keywords":"Coastal; structures; protection; erosion; risk; seawall; groynes; OpenStreetMap ","credit":"Julian O'Grady; Claire Trenham; Rebecca Morris; NESP Knowledge Brokers https://nesp2climate.com.au/science-engagement/","licence":"Licence Defined by Data Provider","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1161","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2024.","rights":"All Rights (including copyright) CSIRO 2024.","published":"2025-10-21T21:36:50.771+11:00","leadResearcher":"Julian O'Grady","serviceCount":0,"contributors":["Claire Trenham","Rebecca Morris","NESP Climate Systems Hub Knowledge Brokers"],"andsPid":"102.100.100/660109","doi":null,"dataRestricted":"TRUE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:7526"},"dataCollectionId":71128,"self":"https://data.csiro.au/dap/ws/v2/collections/71128","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:7526","fileUpload":false,"fileId":0},"title":"CSIRO National Soil Site Database","description":"The CSIRO National Soil Site database (Natsoil) currently contains descriptions from over 40,000 soil site investigations. The data includes morphological descriptions, chemical, physical and mineralogical properties, as well as spectral predictions and soil specimen management data. The database is integral to the The Australian National Soil Archive, provides the foundation for the development of a national soil spectral library and contributes to the TERN Soil Landscapes national soil property modelling. \n\nAll available data is made accessible through the Australian National Soil Information System (ansis.net) or via the JSON API in the Related links section below. This is a live connection to the database and the data that can be accessed is subject to change.\n\nThe database schema is based on the SITES V2 national standard. See supporting files section.\n\n\n","keywords":"Soil Database, Soil Archive, Soil Sites, Chemistry, Morphology","credit":"Data contributed to the database have come from: CSIRO Agriculture and Food, CSIRO Land and Water, CSIRO Ecosystems Science, Department of Agriculture and Food (Western Australia), Department of Land Resource Management (Northern Territory) and Department of Primary Industries, Parks, Water and Environment (Tasmania)","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2025.","rights":"All Rights (including copyright) CSIRO 2025.","published":"2025-11-26T19:24:46.793+11:00","leadResearcher":"CSIRO","serviceCount":0,"contributors":[],"andsPid":"102.100.100/13257","doi":"10.25919/5wm6-xj95","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:64908"},"dataCollectionId":72758,"self":"https://data.csiro.au/dap/ws/v2/collections/72758","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:64908","fileUpload":false,"fileId":0},"title":"Daily 100 m near-surface soil moisture prediction from in-situ data upscaled to Landsat footprint in the Yanco agricultural region during 2016-2021","description":"This collection is structured to support reproducible research for \"Spatial soil moisture prediction from in-situ data upscaled to Landsat footprint: Assessing area of applicability of machine learning models\" (Yu et al., 2025). It provides all necessary input data, trained models, and soil moisture (SM) data extrapolated from 28 OzNet in-situ sites across a primary study area (100 km × 100 km) and an extended area (300 km × 300 km) in southeastern Australia (i.e., the Yanco agricultural region) during 2016-2021. The study period spans a cross-validation period (2016-2019) and an independent test period (2020-2021). The spatial resolution of SM prediction is 100 m and the temporal frequency is daily. A key focus is the characterisation of Area of Applicability (AOA) for Random Forests (RF) and eXtreme Gradient Boosting (XGB) models, delineating where predictions are statistically reliable. The collection includes multiple independent validation datasets from field campaigns, different in-situ networks, and SMAP L2 retrievals for further evaluations.","keywords":"Soil moisture; Spatial prediction; Upscaling; Landsat; Machine learning; Area of applicability","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) The Australian National University, CSIRO, The University of Sydney 2025.","rights":"All Rights (including copyright) The Australian National University, CSIRO, The University of Sydney 2025.","published":"2026-01-04T13:34:40.336+11:00","leadResearcher":"Yi Yu","serviceCount":0,"contributors":["Brendan Malone","Luigi Renzullo","Chad Burton","Siyuan Tian","Ross Searle","Thomas Bishop","Jeffrey Walker"],"andsPid":"102.100.100/705658","doi":"10.25919/dhxv-nz94","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:21172"},"dataCollectionId":73561,"self":"https://data.csiro.au/dap/ws/v2/collections/73561","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:21172","fileUpload":false,"fileId":0},"title":"Greenbushes laterite geochemistry orientation study. LabWest reanalysis 2018 geochemical data.","description":"Geochemical analyses of lateritic cover about the Greenbushes mineralised pegmatite deposit and surrounding terrain. Original analyses were done in the early 1980s. Samples are dominantly of lateritic duricrust (nodular & pisolitic) and loose lateritic pisoliths, lateritic nodules as well as some near-surface bedrock. Major, minor and many trace elements were analysed and are listed. \n\nResults revealed a large (15 km by 30 km), coincident multi-element geochemical halo in lateritic residuum centred on the world class mineralised rare metal pegmatite system. Key elements in the halo are Sn, As, Sb, Nb, Ta, Li, B, Be, Bi ... \n\nPulps which had been used for the original analyses were retrieved from the CSIRO Collection for reanalysis in December 2017 by LABWEST Western Australia providing updated analytical methods, more elements and generally lower limits of detection. ","keywords":"geochemical exploration; laterite geochemistry; Greenbushes pegmatite deposit; multi-element geochemical haloes; mineral exploration; reanalysis by LabWest 2018;","credit":"The initial project was conceived and led by Ray Smith with support by colleagues J L Perdrix, M Barley (in 1982) and J M Davis (in 1983). Reanalyses of original 1979 samples were organised by Tenten Pinchand (CSIRO) and carried out by LABWEST, WA. ","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2017.","rights":"All Rights (including copyright) CSIRO 2017.","published":"2026-03-30T17:00:49.154+11:00","leadResearcher":"Ray Smith","serviceCount":0,"contributors":[],"andsPid":"102.100.100/44200","doi":"10.25919/w9r8-7s36","dataRestricted":"FALSE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:73785"},"dataCollectionId":73785,"self":"https://data.csiro.au/dap/ws/v2/collections/73785","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:73785","fileUpload":false,"fileId":0},"title":"Summer Irrigated Areas and Irrigation Water Use for the Murray-Darling Basin from 1987 to 2024","description":"This dataset provides a 37‑year record (1987–1988 to 2023–2024) of summer irrigated areas and net irrigation water use (IWUnet) across the Murray–Darling Basin (MDB) at ~30 m spatial resolution. Irrigated areas are classified into six phenology‑based types representing major summer crops, pastures and orchards. The products were derived from gap‑free monthly Landsat‑based Normalised Difference Vegetation Index (NDVI) and actual evapotranspiration (ETa) time series, produced using a combination of spatiotemporal gap‑filling and Landsat–MODIS/VIIRS blending. Irrigation phenologies were first identified using Self‑Organising Maps (SOMs) applied to NDVI and ETa time series, and then mapped across the basin for all years using a supervised Pattern Recognition Neural Network (PRNN) (weighted Kappa = 0.91). Irrigation water use (IWUnet) was estimated per pixel using a monthly Thornthwaite–Mather soil water balance, separating green (rainfall-derived) and blue (irrigation-derived) ETa components. Validation was undertaken across multiple spatial scales using flux tower ETa, irrigation district annual reports, agricultural statistics, and MDB‑scale water accounting. Across most regions, both irrigated area and IWUnet exhibited high to moderate accuracy (typically R² > 0.8), with performance reflecting known spatial and temporal patterns in water availability and irrigation dynamics. This dataset provides the first multi-decadal, basin‑wide, high‑resolution record of irrigated extent and water use in the MDB and supports hydrological modelling, irrigation benchmarking, and long-term water resource assessment.","keywords":"Irrigation; evapotranspiration; NDVI; Landsat; CMRSET; Murray–Darling Basin","credit":"The authors acknowledge all people involved in producing, providing and maintaining the data and web portals used in this research. The Murray-Darling Basin Water and Environment Research Program (MD-WERP) Hydrology Theme supported this research. The MD-WERP is an Australian Government initiative to strengthen scientific knowledge of the Murray-Darling Basin that is managed through a partnership between the Department of Agriculture, Water and the Environment, the Commonwealth Environmental Water Holder and the Murray-Darling Basin Authority. CSIRO and TERN Landscapes, part of the Terrestrial Ecosystem Research Network (TERN) supported by the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS), are also acknowledged for the continuous support of CMRSET. Farmer Andrew Watson from Narrabri, NSW is gratefully acknowledged for supporting flux tower measurements in his property.","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2026.","rights":"All Rights (including copyright) CSIRO 2026.","published":"2026-03-30T14:31:22.887+11:00","leadResearcher":"Jorge Pena Arancibia","serviceCount":0,"contributors":["Yingying Yu","Tim McVicar","Tom Van Niel","Francis Chiew","Jamie Vleeshouwer","Aarond Dino"],"andsPid":"102.100.100/733762","doi":"10.25919/te6k-s377","dataRestricted":"TRUE"},{"id":{"identifierType":"Fedora PID","identifier":"csiro:73744"},"dataCollectionId":74142,"self":"https://data.csiro.au/dap/ws/v2/collections/74142","landingPage":{"relationship":"alternate","mediaType":"text/html","href":"https://data.csiro.au/collection/csiro:73744","fileUpload":false,"fileId":0},"title":"Multi- and Hyperspectral satellite imagery supporting HPQ prospectivity analysis of Australia","description":"The aim of this project was to support GA’s HPQ prospectivity analysis by including optical satellite imagery, such as collected by multispectral (e.g. ASTER, Landsat, Sentinel) and hyperspectral (e.g. EMIT, EnMap, PRISMA). For this, CSIRO produced .geotifs of 1) a revised version of the preliminary hyperspectral satellite-derived Al-sheetsilicate abundance index and 2) a satellite multispectral-derived albedo image, both covering the Australian continent. ","keywords":"hyperspectral; multispectral; satellite imagery; critical minerals","licence":"Creative Commons Attribution 4.0 International Licence","licenceLink":{"relationship":"licence","mediaType":"text/html","href":"https://data.csiro.au/dap/ws/v2/licences/1121","fileUpload":false,"fileId":0},"attributionStatement":"All Rights (including copyright) CSIRO 2026.","rights":"All Rights (including copyright) CSIRO 2026.","published":"2026-04-14T19:45:24.293+10:00","leadResearcher":"Carsten Laukamp","serviceCount":0,"contributors":["Ian Lau","Jo Miles","Morgan Williams","Chris Russell","Nastaran Chitsaz","Mike Caccetta"],"andsPid":"102.100.100/733624","doi":"10.25919/htn6-7774","dataRestricted":"FALSE"}]}