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Land suitability data of the Darwin catchments generated by the Northern Australia Water Resource Assessment

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About this Collection

Land suitability data of the Darwin catchments generated by the Northern Australia Water Resource Assessment


These land suitability raster data (in GeoTIFF format) indicates areas of potential suitability for 126 crops and their specific irrigation management systems and seasons in the Darwin catchments. This data provides improved land evaluation information to identify opportunities and promote detailed investigation for a range of sustainable developme... more


Agricultural Spatial Analysis and Modelling


https://doi.org/10.25919/5b8f3a0e8c4a0


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NAWRA Darwin catchments (Northern Territory) Regional development Agriculture, Irrigation Land suitability Agriculture, crops Primary Industry African Mahogany Almond Asian veg Asparagus Avocado Banana Capsicum chilli Cashew Cassava Chia Chickpea Citrus Coffee Cotton Cucurbit Indian Sandalwood Lab lab Lentil Lychee ... more


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Attribution
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Attribution

These suitability raster datasets have been generated from a range of inputs and processing steps. Following is an overview. For more information refer to the CSIRO NAWRA published reports and in particular 'Land suitability of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment, part of the National Water Infrastructure Development Fund: Water Resource Assessments, CSIRO, Australia'. 1. Collated existing data (relating to: soils, climate, topography, natural resources, remotely sensed, of various formats: reports, spatial vector, spatial raster etc). 2. Selection of additional soil and land attribute site data locations by a conditioned Latin hypercube statistical sampling method applied across the covariate data space. 3. Fieldwork was carried out to collect new attribute data, soil samples for analysis and build an understanding of geomorphology and landscape processes. 4. Database analysis was performed to extract the data to specific selection criteria required for the attribute to be modelled. 5. The R statistical programming environment was used for the attribute computing. Models were built from selected input data and covariate data using predictive learning from a Random Forest approach implemented in the ranger R package. 6. Create Digital Soil Mapping (DSM) attribute raster datasets. DSM data is a geo-referenced dataset, generated from field observations and laboratory data, coupled with environmental covariate data through quantitative relationships. It applies pedometrics - the use of mathematical and statistical models that combine information from soil observations with information contained in correlated environmental variables, remote sensing images and some geophysical measurements. 7. Land management options were chosen and suitability rules created for DSM attributes. 8. Suitability rules were run to produce limitation subclass datasets using a modification on the FAO methods. 9. Final suitability data created for all land management options. 10. Companion predicted reliability data was produced. 11. QA Quality assessment of these land suitability data was conducted by two methods; Method 1: Statistical (quantitative) assessment of the "reliability" of the spatial output data presented as a raster of the Confusion Index. Method 2: Collecting independent external validation site data combined with on-ground expert (qualitative) examination of outputs during validation field trips. Across each of the study areas a two week validation field trip was conducted using a new validation site set which was produced by a random sampling design based on conditioned Latin Hypercube sampling using the reliability data of the attribute. The modelled land suitability value was assessed against the actual on-ground value. These results are published in the report cited in this metadata record.


The Australian Government commissioned CSIRO to complete the Northern Australia Water Resource Assessment (NAWRA) - an initiative of the Australian Government’s White Paper on Developing Northern Australia and the Agricultural Competitiveness White Paper, the government’s plan for stronger farmers and a stronger economy. Aspects of the Assessment were undertaken in conjunction with the Northern Territory Government, the Western Australian Government, and the Queensland Government.


Creative Commons Attribution 4.0 International Licence


CSIRO (Australia), Western Australia Department of Agriculture and Food (Australia), Northern Territory Department of Land Resource Management (Australia), Queensland Department of Natural Resources and Mines (Australia), Queensland Department of Environment and Science (Australia)


Thomas, Mark; Gregory, Linda; Harms, Ben; Hill, Jason; Morrison, David; Philip, Seonaid; Searle, Ross; Smolinski, Henry; van Gool, Dennis; Watson, Ian; Wilson, Peter; Wilson, Peter (2018): Land suitability data of the Darwin catchments generated by the Northern Australia Water Resource Assessment. v1. CSIRO. Data Collection. https://doi.org/10.25919/5b8f3a0e8c4a0


All Rights (including copyright) CSIRO 2018.


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

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Location Details

12°1′12″ S


13°51′36″ S


132°39′0″ E


130°0′0″ E


WGS84


About this Project

Northern Australia Basin assessments


This metadata record relates specifically to the stated body of work and was created for the Northern Australia Water Resource Assessment (NAWRA). The NAWRA has undertaken a comprehensive and integrated evaluation of the feasibility, economic viability and sustainability of water resource development in three priority areas in northern Australia: t... more


Ian Watson





Mark Thomas


Linda Gregory


Ben Harms


Jason Hill


David Morrison


Seonaid Philip


Ross Searle


Henry Smolinski


Dennis van Gool


Ian Watson


Peter Wilson


Peter Wilson


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