Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Digital Soil Mapping: A State of the Art

  • Chapter
Digital Soil Mapping with Limited Data

Abstract

Digital Soil Mapping (DSM) can be defined as the creation and population of spatial soil information systems by numerical models inferring the spatial and temporal variations of soil types and soil properties from soil observation and knowledge and from related environmental variables. DSM is now moving toward the operational production of soil maps thanks to a set of researches that have been carried out for the last fifteen years. These researches dealt with various topics: the production and processing of soil covariates, the collection of soil data, the development of numerical models of soil prediction, the evaluation of the quality of digital soil maps and the representation of digital soil maps. The recent advances and open questions within each of these topics are successively examined.

The emergence of DSM as a credible alternative to fulfill the increasing worldwide demand in spatial soil data is conditioned to its ability to (i) increase spatial resolutions and enlarge extents and (ii) deliver a relevant information. The former challenge requires to develop a specific spatial data infrastructure for Digital Soil Mapping, to grasp Digital Soil Mapping onto existing soil survey programs and to develop soil spatial inference systems. The latter challenge requires to map soil function and threats (and not only “primary” soil properties), to develop a framework for the accuracy assessment of DSM products and to introduce the time dimension.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  • Albrecht, C., Huwe, B., Jahn, R., 2007. Chapter 31. Comparison of approaches for automated soil identification. In: P Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 425–436.

    Google Scholar 

  • Baxter, S., Oliver, M., Archer, J.R., 2007. Chapter 35. The spatial distribution and variation of available P in agricultural topsoil in England & Wales in 1971, 1981, 1991 and 2001. In: P Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 477–486.

    Google Scholar 

  • Behrens, T., Scholten, T., 2007. Chapter 25. A comparison of data-mining techniques in predictive soil mapping. In: P Lagacherie, A.B. McBratney and M. Voltz (Eds), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 353–364.

    Google Scholar 

  • Ben-Dor, E., Patkin, K., Banin, A., Karnieli, A., 2002. Mapping of several soil properties using DAIS-7915 hyperspectral scanner data – a case study over clayey soils in Israel. International Journal of Remote Sensing, 23(6), 1043–1062.

    Article  Google Scholar 

  • Bernoux, M., Arrouays, D., Cerri, C.E.P., Cerri C.C., 2007. Chapter 37. Regional organic carbon storage maps of the western Brazilian Amazon based on prior soil maps and geostatistical interpolation. In: P Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 497–506.

    Google Scholar 

  • Boruvka, L., Penizek, V., 2007. Chapter 30. A test of an artificial neural network allocation procedure using the Czech Soil Survey of Agricultural Land data. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 415–424.

    Google Scholar 

  • Brus, D.J., de Gruijter, J.J., Van Groenigen, J.W., 2007. Chapter 14. Designing spatial coverage samples using the k-means clustering algorithm. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 183–192.

    Google Scholar 

  • Bui, E., Simon, D., Schoknecht, N., Payne, A., 2007. Chapter 15. Adequate prior sampling is everything: lessons from the Ord River basin, Australia. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 193–206.

    Google Scholar 

  • Burrough, P., 2007. Chapter 41. The display of digital soil data, 1976–2004. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 555–570.

    Google Scholar 

  • Carré, F., Girard, M.C., 2002. Quantitative mapping of soil types based on regression kriging of taxonomic distances with landform and land cover attributes. Geoderma 110(3,4), 241–263.

    Article  Google Scholar 

  • Chaplot, V., Walter, C., 2007. Chapter 38. Improving the spatial prediction of soils at local and regional levels through a better understanding of soil-landscape relationships: soil hydromorphy in the Armorican Massif of Western France. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 507–522.

    Google Scholar 

  • Cole, N., Boettinger, J., 2007. Chapter 27. Pedogenic understanding raster classification methodology for mapping soils, Powder River Basin, Wyoming. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 377–388.

    Google Scholar 

  • Daroussin, J., King, D., Le Bas, C., Vrscaj, B., Montanarella, L., 2007. Chapter 4. The Soil Geographical Database of Eurasia at scale 1:1 000 000: history and perspective in Digital Soil Mapping. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 55–66.

    Google Scholar 

  • DSM ESBN Working group 2006. Digital Soil Mapping as the support of Production of Functional Soil Maps. Dobos, E., Carré, F., Hengl, T., Reuter, H.I., Tóth, G. (eds). EUR 22123 EN, 68 pp. Office for Official Publications of the European Communities, Luxemburg.

    Google Scholar 

  • Dobermann, A., Simbahan G.C., 2007. Chapter 13. Methodology for using secondary information in sampling optimisation for making fine-resolution maps of soil organic carbon. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 167–182.

    Google Scholar 

  • Dobos, E., Montanarella, L., 2007. Chapter 9. The development of a quantitative procedure for soilscape delineation using digital elevation data for Europe. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 107–118.

    Google Scholar 

  • Dobos, E., Micheli, E., Montanarella, L., 2007. Chapter 36. The population of a 500-m resolution soil organic matter spatial information system for Hungary. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 487–496.

    Google Scholar 

  • Dusart, J., 2007 Chapter 6. Adapting soil mapping practices to the proposed EU INSPIRE directive. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 77–86.

    Google Scholar 

  • Feuerherdt, C., Robinson, N., Williams, S., 2007. Chapter 7. Storage, maintenance and extraction of digital soil data. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 87–96.

    Google Scholar 

  • Finke, P., 2007. Chapter 39. Quality assessment of digital soil maps: producers and users perspectives. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 523–542.

    Google Scholar 

  • Greve, M.H., Greve, M.B., 2007. Chapter 40. Using soil covariates to evaluate and represent the fuzziness of soil map boundaries. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 543–554.

    Google Scholar 

  • Grunwald, S., Ramasundaram, V., Comerford, N.V., Bliss, C.M., 2007. Chapter 42. Are current scientific visualization and virtual reality techniques capable to represent real soil-landscapes? In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 571–580.

    Google Scholar 

  • Hengl, T., Heuvelink, G., Stein, A., 2004. A generic framework for spatial prediction of soil variables based on regression-kriging. Geoderma 120(1–2), 75–93.

    Article  Google Scholar 

  • Heuvelink, G.B.M., Brus, D.J., de Gruijter J.J., 2007. Chapter 11. Optimization of sample configurations for digital mapping of soil properties with universal kriging. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 137–152.

    Google Scholar 

  • Hollingsworth, I., Bui, E., Odeh, I., Ludwig, J., McLeod, P., 2007. Chapter 29. Rule-based land-unit mapping of the Tiwi Islands, Northern Territory, Australia. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 401–414.

    Google Scholar 

  • Howell, D., Kim, Y., Haydu-Houdeshell, C., Clemmer, P., Almaraz, R., Ballmer, M., 2007. Chapter 34. Fitting soil property spatial distribution models in the Mojave Desert for Digital Soil Mapping. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 465–476.

    Google Scholar 

  • Lagacherie, P., Legros, J.P., Burrough, P., 1995. A soil survey procedure using the knowledge of soil pattern established on a previously mapped reference area. Geoderma 65, 283–301.

    Article  Google Scholar 

  • Lagacherie,P., McBratney, A.B., 2007. Chapter 1. Spatial soil information systems and spatial soil inference systems: perspectives for Digital Soil Mapping. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 3–24.

    Google Scholar 

  • Lark, R.M., 2007. Chapter 23. Decomposing digital soil information by spatial scale. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 301–326.

    Google Scholar 

  • Madeira Netto, J.S., Robbez-Masson, J.-M., Martins, E., 2007. Chapter 17. Visible-NIR hyperspectal imagery for discriminating soil types in the la Peyne watershed, France. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 219–234.

    Google Scholar 

  • Mayr, T., Palmer, R., 2007. Chapter 26. Digital Soil Mapping: An England & Wales perspective. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 365–376.

    Google Scholar 

  • Mendonça-Santos, M.L., McBratney, A.B., Minasny, B., 2007. Chapter 21. Soil prediction with spatially decomposed environmental factors. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 269–280.

    Google Scholar 

  • Mermut A.R., Eswaran H., 2000. Some major developments in soil science since the mid-1960s Geoderma 100 (3–4), 403–426.

    Google Scholar 

  • Mérot, P., Squividant, H., Aurousseau, P., Hefting, P., Burt, T., Maitre, V., Kruk, M., Butturini, A., Thenail, C., Viaud, V. 2003. Testing a climato-topographic index for predicting wetlands distribution along an European climate gradient. Ecological Modelling 163(1–2), 51–71.

    Article  Google Scholar 

  • McBratney, A.B., Mendonça Santos, M.L., Minasny, B., 2003. On Digital Soil Mapping. Geoderma 117, 3–52.

    Google Scholar 

  • McKenzie, N., Gallant, J., 2007. Chapter 24. Digital Soil Mapping with improved environmental predictors and models of pedogenesis. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 327–352

    Google Scholar 

  • Minasny, B., McBratney, A.B., 2007. Mechanistic soil–landscape modelling as an approach to developing pedogenetic classifications. Geoderma 133(1–2), 138–149.

    Google Scholar 

  • Minasny, B., McBratney, A.B., 2007. Chapter 12. Latin hypercube sampling as a tool for Digital Soil Mapping. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 153–166.

    Google Scholar 

  • Odeh, I.O.A., Crawford, M., McBratney, A.B., 2007. Chapter 32. Digital mapping of soil attributes for regional and catchment modelling, using covariates, and statistical and geostatistical techniques. In: P Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, volume 31. Elsevier, Amsterdam, pp. 437–454.

    Google Scholar 

  • Robbez-Masson, J.M., 2007. Chapter 19. Producing dynamic cartographic sketches of soilscapes by contextual image processing in order to improve efficiency of pedological survey. In: P Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 245–256.

    Google Scholar 

  • Rossiter, D.G., 2004. Digital soil resource inventories: status and prospects. Soil Use & Management 20(3), 296–301.

    Article  Google Scholar 

  • Saby, N., Arrouays, D., Boulonne, L., Jolivet,C., Pochot, A. 2007. Geostatistical assessment of Pb in soil around Paris, France Science of The Total Environment 367(1,15), 212–221.

    Google Scholar 

  • Saunders, A., Boettinger, J., 2007. Chapter 28. Incorporating Classification Trees into a Pedogenic Understanding Raster Classification Methodology, Green River Basin, Wyoming. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 389–400.

    Google Scholar 

  • Shepherd K.D., Walsh M.G., 2002. Development of reflectance spectral libraries for characterization of soil properties. Soil Science Society America Journal 66, 988–998.

    CAS  Google Scholar 

  • Taylor, J.A., Odeh, I.O.A., 2007. Chapter 33. Comparing discriminant analysis with binomial logistic regression, regression kriging and multi-indicator kriging for mapping salinity risk in northwest New South Wales, Australia. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 455–464.

    Google Scholar 

  • Thwaites, R.N., 2007. Chapter 20. Conceptual and digital soil-landscape mapping using Regolith-Catenary Units. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 257–268.

    Google Scholar 

  • Viscarra Rossel, R.A., Walwoort, D.J.J., Mc Bratney, A.B., Janik, L.K., Skjemstad., J.O. 2006. Visible, near infrared, mid-infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma 131, 59–75.

    Article  CAS  Google Scholar 

  • Walter, C., Lagacherie, P., Follain, S., 2007. Chapter 22. Integrating pedological knowledge into Digital Soil Mapping. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 281–300.

    Google Scholar 

  • Wilford, J., Minty, B., 2007. Chapter 16. The use of airborne gamma-ray imagery for mapping soils and understanding landscape processes. In: P. Lagacherie, A.B. McBratney and M. Voltz (Eds.), Digital Soil Mapping, an introductory perspective. Developments in soil science, vol. 31. Elsevier, Amsterdam, pp. 207–218.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. INRA Laboratoire détude des Interactions Sol Agrosystème Hydrosystème (LISAH), 2 place Viala 34060 Montpellier cedex 1, France

    P. Lagacherie

Authors
  1. P. Lagacherie
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. ISRIC – World Soil Information, 6700 AJ Wageningen, The Netherlands

    Alfred E. Hartemink

  2. Fac. of Agriculture, University of Sydney, McMillan Building A05 Science Rd., NSW Camperdown, Sydney 2006, Australia

    Alex McBratney

  3. EMBRAPA-Brazilian Agricultural Research, Corporation/CNPS-The National Centre of Soil Research, Rua Jardim Botânico. 1024 CEP.22.460-000, Rio de Janeiro-RJ, Brazil

    Maria de Lourdes Mendonça-Santos

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Lagacherie, P. (2008). Digital Soil Mapping: A State of the Art. In: Hartemink, A.E., McBratney, A., Mendonça-Santos, M.d. (eds) Digital Soil Mapping with Limited Data. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-8592-5_1

Download citation

Publish with us

Policies and ethics

Search

Navigation