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Applied and Environmental Soil Science
Volume 2012, Article ID 430347, 17 pages
http://dx.doi.org/10.1155/2012/430347
Research Article

Digital Mapping of Soil Drainage Classes Using Multitemporal RADARSAT-1 and ASTER Images and Soil Survey Data

1Pedology and Precision Agriculture Laboratories, Agriculture and Agri-Food Canada, 979 de Bourgogne Avenue, Local No. 140, Quebec City, QC, Canada G1W 2L4
2Institut National de la Recherche Scientifique, Centre Eau Terre Environnement, 490 Rue de la Couronne, Quebec City, QC, Canada G1K 9A9

Received 26 July 2011; Revised 14 October 2011; Accepted 24 October 2011

Academic Editor: Keith Smettem

Copyright © 2012 Mohamed Abou Niang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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 (0.6S<0.9) were observed for 83% (187 km2) of the study area while 3% of the study area showed very good agreement (S0.9). 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.