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Soil and Landscape Grid Digital Soil Property Maps for South Australia (3" resolution)

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About this Collection

Soil and Landscape Grid Digital Soil Property Maps for South Australia (3" resolution)


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 Ear... more


Soil Sciences not elsewhere classified


https://doi.org/10.4225/08/5aaf39ed26044


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CSIROEnquiries@csiro.au
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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 ... more


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File Naming Conventions


Attributes.html


Download_Options.html


Metadata_References.html


The soil attribute maps are generated using novel spatial modelling and digital soil mapping techniques to disaggregate legacy soil mapping. Legacy soil mapping: Polygon-based soil mapping for South Australia’s agricultural zone was developed via SA’s State Land and Soil Mapping Program (DEWNR 2014, Hall et al. 2009). Sixty one soil classes (termed ‘subgroup soils’) have been defined to capture the range of variation in soil profiles across this area. While legacy soil mapping does not explicitly map the distribution of these soil classes, estimates of their percentage composition and associated soil properties are available for each soil landscape map unit (polygon). Disaggregation of soil classes: The DSMART algorithm (version 1, described in Odgers et al. 2014) was used to produce fine-resolution raster predictions for the probability of occurrence of each soil class. This uses random virtual sampling within each map unit (with sampling weighted by the expected proportions of each soil class) to build predictions for the distribution of soil classes based on relationships with environmental covariate layers (e.g. elevation, terrain attributes, climate, remote sensing vegetation indices, radiometrics). The algorithm was run 100 times then averaged to create probabilistic estimates for soil class spatial distributions. Soil property predictions: The PROPR algorithm (Odgers et al. 2015b) was used to generate soil property maps (and their associated uncertainty) using reference soil property data and the soil class probability maps create through the above DSMART disaggregation step. South Australia’s national- or ASRIS-format soil mapping was used to provide reference soil properties. This dataset was previously developed to meet the specifications of McKenzie et al. (2012) and provides expert soil surveyor estimates for map unit area composition and representative profile properties of approximately 1500 regional variants of the original sixty one ‘subgroup soil’ classes. Equal area depth smoothing splines were applied to the regional variant profile data to obtain property values at the specified GlobalSoilMap depth intervals. Then area-weighted soil property averages were calculated for each subgroup soil class. This process is documented further in Odgers et al. (2015a).


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. This dataset has been produced with significant input from CSIRO; South Australia Department of Environment, Water and Natural Resources; and the University of Sydney.


Creative Commons Attribution 4.0 International Licence


CSIRO (Australia), South Australia Department of Environment, Water and Natural Resources (Australia), University of Sydney (Australia)


Liddicoat, Craig; Holmes, Karen; Maschmedt, David; Rowland, Jan; Searle, Ross; Odgers, Nathan (2014): Soil and Landscape Grid Digital Soil Property Maps for South Australia (3" resolution). v4. CSIRO. Data Collection. https://doi.org/10.4225/08/5aaf39ed26044


All Rights (including copyright) CSIRO 2014.


The metadata and files (if any) are available to the public.

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Location Details

31°36′26.28″ S


38°3′41.2308″ S


141°0′4.824″ E


131°40′57″ E


GDA94


More about this Collection

Peter Wilson


Research Scientist


-2 m




Raster




eng


UTF8


Environment


About this Project

1181.2 TERN Facility No9 InfoGrid GRUNDY


The Soil and Landscape Grid of Australia is a comprehensive fine spatial resolution grid of functional soil attributes and key landscape features across Australia. The landscape attributes are derived from the data collected by the Shuttle Radar Topography Mission, whilst the soil attribute surfaces are modelled from existing soils information. The... more


Mike Grundy


National Soil Grid


The Soil and Landscape Grid of Australia Facility has produced a comprehensive fine-resolution grid of soil attributes and important land surface parameters. The data is consistent with the Specifications of the GlobalSoilMap and is managed as part of the Australian Soil Resource Information System (ASRIS). There are a range of soil attribute produ... more


Modelling


Craig Liddicoat


Karen Holmes


David Maschmedt


Jan Rowland


Ross Searle


Nathan Odgers


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