Digital Soil Mapping

An Introductory Perspective

Edited by

  • Philippe Lagacherie, Institut National de la Recherche Agronomique, Laboratoire sur les Interactions Sol-Agrosystème-Hydrosystème, UMR LISAH AgroM-INRA-IRD, Montpellier, FRANCE
  • Alex McBratney, Faculty of Agriculture, Food & Natural Resources, University of Sydney, NSW, Australia
  • Marc Voltz, Institut National de la Recherche Agronomique, Laboratoire sur les Interactions Sol-Agrosystème-Hydrosystème, UMR LISAH AgroM-INRA-IRD, Montpellier, FRANCE

The book compiles the main ideas and methodologies that have been proposed and tested within these last fifteen years in the field of Digital Soil Mapping (DSM). Begining with current experiences of soil information system developments in various regions of the world, this volume presents states of the art of different topics covered by DSM: Conception and handling of soil databases, sampling methods, new soil spatial covariates, Quantitative spatial modelling, Quality assessment and representation of DSM outputs. This book provides a solid support to students, researchers and engineers interested in modernising soil survey approaches with numerical techniques. It is also of great interest for potential soil data users.
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Soil scientists, physical geographers, ecologists, environmental scientists and planners.


Book information

  • Published: December 2006
  • Imprint: ELSEVIER
  • ISBN: 978-0-444-52958-9


"The editors have undoubtedly brought together a great deal of information...the editors and authors deserve our commendation." - R. Webster in EUROPEAN JOURNAL OF SOIL SCIENCE

Table of Contents

A. Introduction 1. Spatial soil information systems and spatial soil inference systems: perspectives for digital soil mappingP. Lagacherie & A.B. McBratneyB. Digital soil mapping: current state and perspectives 2. A review of digital soil mapping in AustraliaElisabeth Bui3. The state of the art of Brazilian soil mapping and prospects for digital soil mapping Lou Mendonca et al.4. The Soil Geographical Database of Eurasia at scale 1:1 000 000: history and perspective in digital soil mapping Joël Daroussin, Dominique King, Christine Le Bas, Borut Vrscaj & Luca Montanarella5. Developing a Digital Soil Map for Finland. Harri Lilja & Raimo NevalainenC. Conception and handling of soil databases 6. Adapting soil mapping practices to the proposed EU INSPIRE directive. Jean Dusart7. Storage, maintenance and extraction of digital soil data Craig Feuerherdt, Nathan Robinson & Steve Williams8. Towards a soil information system for uncertain data.Gerard Heuvelink & James Brown9. The development of a quantitative procedure for soilscape delineation using digital elevation data for Europe.Endre Dobos & Luca Montanarella10. Ontology-based multi-source data integration for digital soil mapping .Bart Krol, David Rossiter & Wouther SideriusD. Sampling methods for creating digital soil maps 11. Optimization of sample configurations for digital mapping of soil properties withuniversal krigingGerard B.M. Heuvelink, D.J. Brus & J.J. de Gruijter12. Latin hypercube sampling as a tool for digital soil mappingBudiman Minasny & Alex. B. McBratney13. Methodology for using secondary information in sampling optimisation for making fine-resolution maps of soil organic carbon Achim Dobermann & Gregorio C. Simbahan14. Designing spatial coverage samples using the k-means clustering algorithmD.J Brus, J.J. de Gruijter & J.W. Van Groenigen15. Adequate prior sampling is everything: lessons from the Ord River basin, Australia.Elisabeth Bui, David Simon, Noël Schoknecht & Alan PayneE. New environmental covariates for digital soil mapping 16. The use of airborne gamma-ray imagery for mapping soils and understanding landscape processesJohn Wilford & Brian Minty17. Visible-NIR hyperspectal imagery for discriminating soil types in the la Peyne watershed, France J.S. Madeira Netto, J.-M. Robbez-Masson & E. Martins18. Land-cover classification from Landsat imagery for mapping dynamic wet and saline soils S. Kienast-Brown & J.L. Boettinger19.. Producing dynamic cartographic sketches of soilscapes by contextual image processing in order to improve efficiency of pedological survey J.-M. Robbez-Masson20. Conceptual and digital soil-landscape mapping using Regolith-Catenary UnitsRobin N. Thwaites21. Soil prediction with spatially decomposed environmental factors M.L. Mendonça-Santos, A.B. McBratney & B. MinasnyF. Quantitative modelling for digital soil mapping 22. Integrating pedological knowledge into digital soil mapping C. Walter, P. Lagacherie & S. Follain23. Decomposing digital soil information by spatial scale R.M. Lark24 Digital soil mapping with improved environmental predictors and models of pedogenesis. Neil MacKenzie & J. GallantF.i : Examples of predicting soil classes 25. A comparison of data-mining techniques in predictive soil mapping. Thorsten Behrens, Helga Foerster & Thomes Scholten26. Digital soil mapping: an England & Wales perspective.Thomas Mayr & Robert Palmer27. Pedogenic Understanding Raster Classification Methodology for Mapping Soils, Powder River Basin, Wyoming, USA Nephi Cole & Janis Boettinger28. Incorporating Classification Trees into a Pedogenic Understanding Raster Classification Methodology, Green River Basin, Wyoming, USA Amy Saunders & Janis Boettinger29. Rule-based land-unit mapping of the Tiwi Islands, Northern Territory, Australia. Ian Hollingsworth, Elisabeth Bui, Inakwu Odeh, John Ludwig & P. McLeod30. A test of an artificial neural network allocation procedure using the Czech Soil Survey of Agricultural Land data. Lubos Boruvka & Vit Penizek31. Comparison of approaches for automated soil identification. Christoph Albrecht, Bernd Huwe & Reinhold JahnF.ii : Examples of predicting soil attributes 32. Digital mapping of soil attributes for regional and catchment modelling, using covariates, and statistical and geostatistical techniquesInakwu O.A. Odeh, Mark Crawford & Alex. B. McBratney33. Comparing discriminant analysis with binomial logistic regression, regression kriging and multi-indicator kriging for mapping salinity risk in northwest New South Wales, AustraliaJames A. Taylor & Inakwu O.A. Odeh34. Fitting soil property spatial distribution models in the Mojave Desert for digital soil mapping D. Howell, Y. Kim, C. Haydu-Houdeshell, P. Clemmer, R. Almaraz & M. Ballmer 35. The spatial distribution and variation of available P in agricultural topsoil in England & Wales in 1971, 1981, 1991 and 2001Samantha Baxter, Margaret Oliver & John R. Archer36. The population of a 500-m resolution soil organic matter spatial information system for HungaryE. Dobos, E. Micheli & L. Montanarella 37. Regional organic carbon storage maps of the western Brazilian Amazon based on prior soil maps and geostatistical interpolation M. Bernoux, D. Arrouays, C. E. P. Cerri & C. C. Cerri38. 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 FranceV. Chaplot & C. WalterG Quality assessment and representation of digital soil maps39. Quality assessment of digital soil maps: producers and users perspectives.Peter Finke40. Using soil covariates to evaluate and represent the fuzziness of soil map boundaries M.H. Greve & M.B. Greve41 The display of digital soil data, 1976-2004. Peter Burrough42 Are Current Scientific Visualization and Virtual Reality Techniques Capable to Represent Real Soil-Landscapes?Sabine Grunwald, Vinay Ramasundaram, Nicholas B. Comerford & Christine M. Bliss