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Digital mapping of soil drainage classes using multitemporal RADARSAT-1 and ASTER images and soil survey data.

Niang, Mohamed Abou; Nolin, Michel C.; Bernier, Monique; Perron, Isabelle (2012). Digital mapping of soil drainage classes using multitemporal RADARSAT-1 and ASTER images and soil survey data. Applied and Environmental Soil Science , vol. 2012 . p. 430347. DOI: 10.1155/2012/430347.

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Résumé

Discriminant analysis classification (DAC) and decision tree classifiers (DTC) were used for digital mapping of soil drainage in the Bras-d'Henri watershed (QC, Canada) using earth observation data (RADARSAT-1 and ASTER) and soil survey dataset. Firstly, a forward stepwise selection was applied to each land use type identified by ASTER image in order to derive an optimal subset of soil drainage class predictors. The classification models were then applied to these subsets for each land use and merged to obtain a digital soil drainage map for the whole watershed. The DTC method provided better classification accuracies (29 to 92%) than the DAC method (33 to 79%) according to the land use type. A similarity measure (S) was used to compare the best digital soil drainage map (DTC) to the conventional soil drainage map. Medium to high similarities (0.6≤S<0.9) were observed for 83% (187 km²) of the study area while 3% of the study area showed very good agreement (S≥0.9). Few soil polygons showed very weak similarities (S<0.3). This study demonstrates the efficiency of combining radar and optical remote sensing data with a representative soil dataset for producing digital maps of soil drainage.

Type de document: Article
Mots-clés libres: sol; drainage; enquête pédologique; cartographie numérique
Centre: Centre Eau Terre Environnement
Date de dépôt: 19 nov. 2020 21:19
Dernière modification: 19 nov. 2020 21:19
URI: http://espace.inrs.ca/id/eprint/7247

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