Processing...

Soil drainage DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

Tools Click here to view this collection in the new DAP user interface

show summary fields  |   show all    
Tools



About this Collection

Soil drainage DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment


Soil drainage is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). Soil drainage describes local soil wetness conditions (rate of water movement from the site soil profile). This soil drainage raster data repres... more


Agricultural Spatial Analysis and Modelling


https://doi.org/10.25919/5b8f22a214acf


CSIRO Enquiries
CSIROEnquiries@csiro.au
1300 363 400

NAWRA Fitzroy catchment (Western Australia) Darwin catchments (Northern Territory) Mitchell catchment (Queensland) Soil drainage Drainage Soil Digital soil mapping Agriculture Land suitability


:

NAWRA spatial data explorer

:

NAWRA website including reports

:

Browse other NAWRA datasets

Attribution
:

Search for NAWRA publications

Attribution

This soil drainage dataset has 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 'Digital soil mapping 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 2018'. 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 soil drainage Digital Soil Mapping (DSM) attribute raster dataset. 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. Companion predicted reliability data was produced from the 500 individual Random Forest attribute models created. 8. QA Quality assessment of this DSM attribute data was conducted by three methods. Method 1: Statistical (quantitative) method of the model and input data. Testing the quality of the DSM models was carried out using data withheld from model computations and expressed as OOB and R squared results, giving an estimate of the reliability of the model predictions. These results are supplied. Method 2: Statistical (quantitative) assessment of the spatial attribute output data presented as a raster of the attributes “reliability”. This used the 500 individual trees of the attributes RF models to generate 500 datasets of the attribute to estimate model reliability for each attribute. For categorical attributes the method for estimating reliability is the Confusion Index. This data is supplied. Method 3: 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 DSM attribute 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; Brough, Dan; Bui, Elisabeth; Harms, Ben; Hill, Jason; Holmes, Karen; Morrison, David; Philip, Seonaid; Searle, Ross; Smolinski, Henry; Tuomi, Seija; van Gool, Dennis; Watson, Ian; Wilson, Peter; Wilson, Peter (2018): Soil drainage DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment. v1. CSIRO. Data Collection. https://doi.org/10.25919/5b8f22a214acf


All Rights (including copyright) CSIRO 2018.


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

show all

Location Details

12°1′12″ S


19°21′0″ S


145°33′0″ E


123°2′60″ 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


Dan Brough


Elisabeth Bui


Ben Harms


Jason Hill


Karen Holmes


David Morrison


Seonaid Philip


Ross Searle


Henry Smolinski


Seija Tuomi


Dennis van Gool


Ian Watson


Peter Wilson


Peter Wilson


Similar collections

  • Gilgai microrelief DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment....
    view
  • Rockiness DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment....
    view
  • Soil surface pH DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment....
    view
  • Soil surface texture DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment....
    view

Others were also interested in

  • Gilgai microrelief DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment....
    view
  • Soil surface structure DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment....
    view
  • Soil surface texture DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment....
    view
  • Rockiness DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment....
    view