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Regional mapping of soil parent material by machine learning based on point data

Marine Lacoste Blandine Lemercier 1 Christian Walter 1
1 SAS - Sol Agro et hydrosystème Spatialisation
Abstract : A machine learning system (MART) has been used to predict soil parent material (SPM) at the regional scale with a 50-m resolution.The use of point-specific soil observations as training data was tested as a replacement for the soil maps introduced in previous studies, with the aim of generating a more even distribution of training data over the study area
Keywords : boosted regression trees classification tree analysis classification tree Pedogenesis factor Soil parent materiaLandDigital soil mapping Regional scale Boosted environmentaLandcorrelation spatial prediction gradient landscape models scales map susceptibility
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Submitted on : Friday, September 7, 2012 - 3:31:09 PM
Last modification on : Wednesday, April 6, 2022 - 4:08:09 PM

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AGROCAMPUS-OUEST | UNAM | INRA | AGROCAMPUS-OUEST-UMR-SAS | INRAE | UMR-SAS

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Marine Lacoste, Blandine Lemercier, Christian Walter. Regional mapping of soil parent material by machine learning based on point data. Geomorphology, Elsevier, 2011, 133 (1-2), pp.90-99. ⟨10.1016/j.geomorph.2011.06.026⟩. ⟨hal-00729273⟩

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