This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.
This is Version 1 of the Australian Soil Clay product of the Soil and Landscape Grid of Australia.
The 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 (approximately 90 x 90 m pixels).
These maps are generated by combining the best available Digital Soil Mapping (DSM) products available across Australia.
Attribute Definition: 2 micrometre mass fraction of the less than 2 mm soil material determined using the pipette method;
Period (temporal coverage; approximately): 1950-2013;
Spatial resolution: 3 arc seconds (approx 90m);
Total number of gridded maps for this attribute: 18;
Number of pixels with coverage per layer: 2007M (49200 x 40800);
Total size before compression: about 8GB;
Total size after compression: about 4GB;
Data license : Creative Commons Attribution 3.0 (CC By);
Target data standard: GlobalSoilMap specifications;
The National Digital Soil Property Maps are generated by combining the best available digital soil mapping to calculate a variance weighted mean for each pixel. Two DSM methods have been utilised across and in various parts of Australia, these being:
1) Decision trees with piecewise linear models with kriging of residuals developed from soil site data across Australia. (Viscarra Rossel et al., 2014a); 2) Disaggregation of existing polygon soil mapping using DSMART (Odgers et al. 2014a). Version 1 of the National Digital Soil Property Maps combines mapping from the: 1) Australia-wide three-dimensional Digital Soil Property Maps; 2) Western Australia Polygon Disaggregation Maps; 3) South Australian Agricultural Areas Polygon Disaggregation Maps; 4) Tasmanian State-wide DSM Maps. These individual mapping products are also available in the CSIRO Data Access Portal (https://data.csiro.au). Please refer to these individual products for more detail on the DSM methods used. References: Specifications: Version 1 GlobalSoilMap.net products, Release 2.1, viewed 12/09/2014, http://www.globalsoilmap.net/specifications. Bishop, TFA, McBratney, AB & Laslett, GM 1999, 'Modelling soil attribute depth functions with equal-area quadratic smoothing splines', Geoderma, vol. 91, no. 1-2, pp. 27-45. http://dx.doi.org/10.1016/S0016-7061(99)00003-8. Breiman, L, Friedman, J, Stone, CJ & Olshen, RA 1984, Classification and Regression Trees, Wadsworth statistics/probability series, Wadsworth Belmont, Ca. Clifford, D, Dobbie, MJ & Searle, R 2014, 'Non-parametric imputation of properties for soil profiles with sparse observations', Geoderma, vol. 232-234, pp. 10-8. http://dx.doi.org/10.1016/j.geoderma.2014.04.026. Clifford, D, Searle, R & Holmes, KW 2015, 'Methods to merge disparate spatial estimates of soil attributes', Soil Research, in preparation. de Caritat, P & Cooper, M 2011, National Geochemical Survey of Australia: The Geochemical Atlas of Australia, Geoscience Australia, Record 2011/20 (2 Volumes), Canberra, 557 pp. http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_71973. DEWRN 2014, Mapping soil and land, Department of Environment, Water and Natural Resources, Government of South Australia, viewed 14/04/2014, http://www.environment.sa.gov.au/Knowledge_Bank/Information_data/soil-and-land/mapping-soil-and-land. Grunwald, S 2009, 'Multi-criteria characterization of recent digital soil mapping and modeling approaches', Geoderma, vol. 152, no. 3-4, pp. 195-207. http://dx.doi.org/10.1016/j.geoderma.2009.06.003. Hall, JAS, Maschmedt, DJ & Billing, NB 2009, The Soils of Southern South Australia, The South Australian Land and Soil Book Series, Volume 1; Geological Survey of South Australia, Bulletin 56, Volume 1, Department of Water, Land and Biodiversity Conservation, Government of South Australia. https://data.environment.sa.gov.au/Land/Land-Resources/Pages/Home.aspx. Holmes, KW, Griffin, TG & Odgers, NP 2015, 'Continental scale spatial disaggregation of legacy soil maps: evaluation over Western Australia', Soil Research, in preparation. Jacquier, D, Wilson, P, Griffin, T & Daniel, B 2012, Soil Information Transfer and Evaluation System (SITES) - Database design and exchange protocols, CSIRO Land and Water, Canberra. http://www.clw.csiro.au/aclep/publications/reports.htm. Kidd, D 2015, '80-metre Resolution 3D Soil Attribute Maps for Tasmania', Soil Research, in preparation. Kidd, DB, Malone, BP, McBratney, AB, Minasny, B & Webb, MA 2014, 'Digital mapping of a soil drainage index for irrigated enterprise suitability in Tasmania, Australia', Soil Research, vol. 52, no. 2, pp. 107-19. http://dx.doi.org/10.1071/sr13100. Malone, BP, Minasny, B, Odgers, NP & McBratney, AB 2014, 'Using model averaging to combine soil property rasters from legacy soil maps and from point data', Geoderma, vol. 232, pp. 34-44. http://dx.doi.org/10.1016/j.geoderma.2014.04.033. McBratney, AB, Mendonça Santos, ML & Minasny, B 2003, 'On digital soil mapping', Geoderma, vol. 117, no. 1-2, pp. 3-52. http://dx.doi.org/10.1016/S0016-7061(03)00223-4. McKenzie, NJ, Jacquier, DW, Maschmedt, DJ, Griffin, EA & Brough, DM 2012, The Australian Soil Resource Information System (ASRIS) Technical Specifications, Revised Version 1.6, June 2012, The Australian Collaborative Land Evaluation Program. http://www.asris.csiro.au/downloads/ASRIS_Tech_Specs_201.6.pdf. McKenzie, NJ & Ryan, PJ 1999, 'Spatial prediction of soil properties using environmental correlation', Geoderma, vol. 89, no. 1-2, pp. 67-94. http://dx.doi.org/10.1016/s0016-7061(98)00137-2. Odgers, NP, Holmes, KW, Griffin, T & Liddicoat, C 2015a, 'Derivation of soil attribute estimations from legacy soil maps', Soil Research, in preparation. Odgers, NP, McBratney, AB & Minasny, B 2015, 'Digital soil property mapping and uncertainty estimation using soil class probability rasters', Geoderma, vol. 237-238, pp. 190-8. http://dx.doi.org/10.1016/j.geoderma.2014.09.009. Odgers, NP, Sun, W, McBratney, AB, Minasny, B & Clifford, D 2014, 'Disaggregating and harmonising soil map units through resampled classification trees', Geoderma, vol. 214-215, pp. 91-100. http://dx.doi.org/10.1016/j.geoderma.2013.09.024. Rodríguez, E, Morris, CS & Belz, JE 2006, 'A Global Assessment of the SRTM Performance', Photogrammetric Engineering & Remote Sensing, vol. 72, no. 3, pp. 249-60. Schoknecht, N & Pathan, S 2013, Soil groups of Western Australia: a simple guide to the main soils of Western Australia, 4th ed. Resource Management Technical Report 280, Department of Agriculture and Food Western Australia, Perth. http://archive.agric.wa.gov.au/PC_95446.html. Schoknecht, N, Tille, P & Purdie, B 2004, Soil-landscape mapping in south-western Australia: an overview of methodology and outputs, Resource Management Technical Report 280, Department of Agriculture, Government of Western Australia, Perth. Searle, R 2014, 'The Australian Site Data Collation to Support Global Soil Map', paper presented to GlobalSoilMap Conference 2013, Orleans, France, 7-9 October 2013, https://publications.csiro.au/rpr. Viscarra Rossel, RA 2011, 'Fine-resolution multiscale mapping of clay minerals in Australian soils measured with near infrared spectra', Journal of Geophysical Research: Earth Surface, vol. 116, no. F4, p. F04023. http://dx.doi.org/10.1029/2011JF001977. Viscarra Rossel, RA & Chen, C 2011, 'Digitally mapping the information content of visible-near infrared spectra of surficial Australian soils', Remote Sensing of Environment, vol. 115, no. 6, pp. 1443-55. http://dx.doi.org/10.1016/j.rse.2011.02.004. Viscarra Rossel, RA, Chen, C, Grundy, M, Searle, R, Clifford, D & Campbell, PH 2015a, 'The Australian three-dimensional soil grid: Australia's contribution to the GlobalSoilMap project', Soil Research, in preparation. Viscarra Rossel, RA, Chen, H & Hicks, W 2015b, 'Prediction of spatial distribution of soil attributes to depth from Australian site and covariate data', Soil Research, in preparation. Viscarra Rossel, RA & Webster, R 2012, 'Predicting soil properties from the Australian soil visible-near infrared spectroscopic database', European Journal of Soil Science, vol. 63, no. 6, pp. 848-60. http://dx.doi.org/10.1111/j.1365-2389.2012.01495.x. Viscarra Rossel, RA, Webster, R, Bui, EN & Baldock, JA 2014, 'Baseline map of organic carbon in Australian soil to support national carbon accounting and monitoring under climate change', Global Change Biology, vol. 20, no. 9, pp. 2953-70. http://dx.doi.org/10.1111/gcb.12569.
CSIRO (2014) Soil and Landscape Grid National Soil Attribute Maps - Clay 3 resolution - Release 1. Bioregional Assessment Source Dataset. Viewed 12 March 2019, http://data.bioregionalassessments.gov.au/dataset/f8640540-4bb7-42ee-995a-219881e67705.