Thematic map comparison: evaluating the statistical significance of differences in classification accuracy
Photogrammetric Engineering and Remote Sensing, 70, (5), .
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A methodology for landslide susceptibility mapping using an integrated remote sensing and GIS approach is presented. A part of the Darjeeling Himalaya was selected for the model execution. IRS satellite data, topographic maps, field data, and other informative maps were used as inputs to the study. Important terrain factors, contributing to landslide occurrences in the region, were identified and corresponding thematic data layers were generated. These data layers represent the geological, topographical, and hydrological conditions of the terrain. A numerical rating scheme for the factors was developed for spatial data analysis in a GIS. The resulting landslide susceptibility map delineates the area into different zones of four relative susceptibility classes: high, moderate, low, and very low. The susceptibility map was validated by correlating the landslide frequencies of different classes. This has shown a close agreement with the existing field instability condition. The effectiveness of the map was also confirmed by the high statistically significant value of a chi-square test.
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