References

Recent publications

• Ross Searle, Alexander McBratney, Mike Grundy, Darren Kidd, Brendan Malone, Dominique Arrouays, Uta Stockman, Peter Zund, Peter Wilson, John Wilford, Dennis Van Gool, John Triantafilis, Mark Thomas, Liz Stower, Brian Slater, Nathan Robinson, Anthony Ringrose-Voase, Jose' Padarian, Jim Payne, Thomas Orton, Nathan Odgers, Lauren O'brien, Budiman Minasny, John McLean Bennett, Craig Liddicoat, Edward Jones, Karen Holmes, Ben Harms, Jonathan Gray, Elisabeth Bui, Kaitlyn Andrews. (2021) Digital soil mapping and assessment for Australia and beyond: A propitious future. Geoderma Regional 24, e00359. https://www.sciencedirect.com/science/article/pii/S2352009421000043


• Darren Kidd, Ross Searle, Mike Grundy, Alex McBratney, Nathan Robinson, Lauren O'Brien, Peter Zund, Dominique Arrouays, Mark Thomas, Joe' Padarian, Edward Jones, John McLean Bennett, Budiman Minasny, Karen Holmes, Brendan P Malone, Craig Liddicoat, Elizabeth A Meier, Uta Stockmann, Peter Wilson, John Wilford, Jim Payne, Anthony Ringrose-Voase, Brian Slater, Nathan Odgers, Jonathan Gray, Dennis van Gool, Kaitlyn Andrews, Ben Harms, Liz Stower, John Triantafilis (2020) Operationalising digital soil mapping - Lessons from Australia. Geoderma Regional 23, e00335 https://www.sciencedirect.com/science/article/pii/S2352009420300845


• Michael J Grundy, Ross Searle, Elizabeth A Meier, Anthony J Ringrose-Voase, Darren Kidd, Thomas G Orton, John Triantafilis, Seonaid Philip, Craig Liddicoat, Brendan Malone, Mark Thomas, Jonathan Gray, John McLean Bennett. (2020). Digital soil assessment delivers impact across scales in Australia and the Philippines. Geoderma Regional 22, e00314 https://www.sciencedirect.com/science/article/pii/S2352009420300638


• B Malone, R Searle. (2020) Improvements to the Australian national soil thickness map using an integrated data mining approach. Geoderma 377, 114579 https://www.sciencedirect.com/science/article/pii/S0016706119328630


• B Malone, R Searle. (2021). Updating the Australian digital soil texture mapping (Part 1*): re-calibration of field soil texture class centroids and description of a field soil texture conversion algorithm. Soil Research 59 (5), 419-434 https://www.publish.csiro.au/sr/SR20283


• B Malone, R Searle (2021). Updating the Australian digital soil texture mapping (Part 2*): spatial modelling of merged field and lab measurements. Soil Research 59 (5), 435-451 https://www.publish.csiro.au/sr/sr20284


• Mercedes Roman Dobarco, Alexandre M Wadoux, Brendan Malone, Budiman Minasny, Alex B McBratney, Ross Searle. (2022) Mapping soil organic carbon fractions for Australia, their stocks and uncertainty. Biogeosciences Discussions, 1-38 https://www.publish.csiro.au/sr/sr20284


• Specifications: Version 1 GlobalSoilMap.net products, Release 2.1, viewed 12/09/2014, <GlobalSoilMap 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. <https://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. <https://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. <https://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, <https://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. <https://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. <https://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. <https://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. <https://dx.doi.org/10.1016/j.geoderma.2014.04.033>.
  


• McBratney, AB, Mendonia Santos, ML & Minasny, B 2003, 'On digital soil mapping', Geoderma, vol. 117, no. 1-2, pp. 3-52. <https://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. <https://www.asris.csiro.au/downloads/ASRIS%20Tech%20Specs%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. <https://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. <https://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. <https://dx.doi.org/10.1016/j.geoderma.2013.09.024>.
  


• Rodriguez, 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. <https://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/pub?pid=csiro:EP139009>.
  


• 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. <https://dx.doi.org/10.1029/2011JF001977>.
  


• Viscarra Rossel, RA, Chen, C, Grundy, M, Searle, R, Clifford, D & Campbell, PH 2015, 'The Australian three-dimensional soil grid: Australia's contribution to the GlobalSoilMap project', Soil Research, in preparation.
  
• Viscarra Rossel, RA, Chen, H & Hicks, W 2015, 'Prediction of spatial distribution of soil attributes to depth from Australian site and covariate data', Soil Research, in preparation.
  


• 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. <https://dx.doi.org/10.1016/j.rse.2011.02.004>.
  


• 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. <https://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. <https://dx.doi.org/10.1111/gcb.12569>.

 

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