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

M. Lacoste; Blandine Lemercier; Christian Walter

doi:10.1016/j.geomorph.2011.06.026

Journal articles

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

M. 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

Document type :

Journal articles

Domain :

Environmental Sciences / Science des sols

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https://hal-agrocampus-ouest.archives-ouvertes.fr/hal-00729273
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Submitted on : Friday, September 7, 2012 - 3:31:09 PM
Last modification on : Friday, October 9, 2020 - 2:10:05 PM

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

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

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