Regional mapping of soil parent material by machine learning based on point data
Authors:
- Marine LacosteMLMarine Lacoste
- Blandine LemercierBLBlandine Lemercier
- Christian WalterCWChristian Walter
- 1 October 2011
- journal article
- research article
- Published by Elsevier in Geomorphology
- Vol. 133 (1-2) , 90-99
Abstract
No abstract availableKeywords
This publication has 50 references indexed in Scilit:
- Instance selection and classification tree analysis for large spatial datasets in digital soil mappingGeoderma, 2008
- Australia-wide predictions of soil properties using decision treesGeoderma, 2005
- On digital soil mappingGeoderma, 2003
- A strategy to fill gaps in soil survey over large spatial extents: an example from the Murray–Darling basin of AustraliaGeoderma, 2003
- Integrating forest soils information across scales: spatial prediction of soil properties under Australian forestsForest Ecology and Management, 2000
- Predicting soil classes with parameters derived from relief and geologic materials in a sandstone region of the Vosges mountains (Northeastern France)Geoderma, 1999
- Spatial prediction of soil properties using environmental correlationGeoderma, 1999
- A soil survey procedure using the knowledge of soil pattern established on a previously mapped reference areaGeoderma, 1995
- Direct induction of compact rule-based classifiers for resource mappingInternational Journal of Geographical Information Science, 1994
- A Coefficient of Agreement for Nominal ScalesEducational and Psychological Measurement, 1960