A land-cover classification for landslide susceptibility mapping by using feature components

2006-06-20
YESİLNACAR, ERTAN
Süzen, Mehmet Lütfi
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Classifying original bands and/or image components may cause unsatisfactory results in fields that have heterogeneous reflectance. In such cases, the demand for accurate land-use, land-cover, vegetation, and forestry information may require more specific components. The components should represent peculiar information collected from several inputs for target land covers. In this study, a new technique of land-cover classification was explored to prepare an input which increases the success of landslide susceptibility mapping in a subtropical region, Asarsuyu Catchment Area (Duzce). Land-cover mapping is a difficult issue in this area by only carrying out field studies and aerial-photo interpretations. Moreover, applying different classifications of Landsat Thematic Mapper bands and/or their secondary products does not produce acceptable results. For this reason, vegetation indices, soil/surface moisture indices, topographic wetness index and drainage density were calculated to produce feature representative components for the land-cover classification process. Results obtained from the proposed technique show that feature representative components significantly improve the conventional classification accuracy from 77% to 89% and the resultant land-cover map is such a valuable input for landslide susceptibility mapping that it increases the success of the landslide susceptibility map from 63% to 88%.
Information-systems, Gis, Water, Index, Integration, Vegetation
https://hdl.handle.net/11511/45065
INTERNATIONAL JOURNAL OF REMOTE SENSING
Department of Geological Engineering, Article

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Citation Formats
E. YESİLNACAR and M. L. Süzen, “A land-cover classification for landslide susceptibility mapping by using feature components,” INTERNATIONAL JOURNAL OF REMOTE SENSING, pp. 253–275, 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/45065.
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