Top 5 books, articles and free sources for studying DSM

Submitted by t.hengl on August 24, 2010 - 13:35


DSM books

I was asked by Ronald Vargas to recommend some key literature that can be used to promote DSM approaches to soil modeling and mapping. They would like to ditribute some of these literature sources at the LAC workshop. To make the list short enough, I have put top 5 sources in three categories: best books, best articles and best on-line materials (lecture notes). Of course, I am heavily biased towards free and open source tools R and OSGeo. Another way to find the most influential publications is to look at the most cited articles/books. If you are more interested in more classical papers about pedometrics, take a look at Alex McBratney's selection of best papers.


  1. Boettinger, J., Howell, D., Moore, A., Hartemink, A., & Kienast-Brown, S. (Eds.) 2010. Digital Soil Mapping: Bridging Research, Environmental Application, and Operation. volume 2 of Progress in Soil Science. Springer. --- The conference proceedings from the third Global workshop on DSM.
  2. McKenzie, N.J. Grundy, M.J. Webster, R. 2008. Guidelines for Surveying Soil and Land Resources. Csiro Publishing, Canberra, 557 p. --- This is probably the most extensive and most up-to-date cook-book on soil surveying. It has an excellent geostatistician on the team, hence certainly worth obtaining.
  3. Lagacherie, P., McBratney, A. B., Voltz, M., 2005. Digital soil mapping: an introductory perspective. Amsterdam, Elsevier, 600 p. --- The conference proceedings from the first Global workshop on DSM.
  4. Reimann, C., Filzmoser, P., Garrett, R., Dutter, R., 2008. Statistical Data Analysis Explained Applied Environmental Statistics with R. Wiley, Chichester, 337 p. --- This book basically uses soil data to demonstrate statistical analysis and visualization steps using R. The R code and graphics is also available from the book's homepage.
  5. Bivand, R., Pebesma, E., Rubio, V., 2008. Applied Spatial Data Analysis with R. Use R Series, Springer, Heidelberg, pp. 378. --- This is book is by many considered to be the bible of spatial data analysis using open source tools: R and open source GIS. A must-read!

Journal articles

  1. McBratney, A. B., Mendoca Santos, M. L., & Minasny, B. 2003. On digital soil mapping (0). Geoderma, 117, 3–52. --- Although a bit outdated, this is still considered to be one of the most extensive reviews of DSM. Alex introduced his SCORPAN model and tried to systematize the field as much as possible.
  2. Beaudette, D., & O’Geen, A., 2009. Soil-web: An online soil survey for California, Arizona, and Nevada (0). Computers & Geosciences, 35:2119-2128 --- This is an excellent paper by Dylan and his supervisor reviewing on-line soil survey functionality - how to get soil data out and make them more usable.
  3. Behrens, T., and Scholten, T., 2006. Digital soil mapping in Germany - a review. Journal of Plant Nutrition and Soil Science 169(3): 434–443. --- Although focused on Germany only, this paper gives an excellent overview of trends in DSM.
  4. Minasny, B., & McBratney, A. B., 2007. Spatial prediction of soil properties using EBLUP with Matern covariance function. Geoderma, 140, 324–336. --- An excellent review paper of spatial prediction techniques used to map soil variables. This shows that regression-kriging is the method to use for soil mapping.
  5. Henderson, B.L., Bui, E.N., Moran, C.J. and Simon, D.A.P., 2005. Australia-wide predictions of soil properties using decision trees. Geoderma, 124(3-4): 383-398. --- The group from Australia demonstrate how to produce continental scale soil maps using point data and regression trees.

*see also: Best paper awards by the Pedometrics society.

Free materials / lecture notes

  1. Open Source Software Tools for Soil Scientists, University of California at Davis. --- this is a collection of live articles by Dylan Beaudette and colleagues from the California Soil Resource Lab. The examples are adjusted to USDA data mainly, but certainly the most extensive and most complete guide to DSM using FOSS tools.
  2. Lecture Notes & Links, Compiled by David G. Rossiter --- David has been running courses on using R for statistical analysis of soil and environmental data for almost half decade. All his materials (uncluding R codes and sample data sets) are available to the public. David also regularly updates his materials so you will be using the state-of-the-art tools.
  3. GEOSTAT course materials --- Complete course materials for the GEOSTAT summer school course on spatial data analysis using FOSS.
  4. Dylan's blog --- This is a collection of easy to follow articles that can certaintly promote use of open source tools for DSM applications.
  5. The Soil Data Mart --- A collection of data and documents developed by NRCS. 

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