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Landslide Susceptibility Analysis : SVM Application of Spatial Databases Considering Clay Mineral Index Values Extracted from an ASTER Satellite Image
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  • Journal title : The Journal of Engineering Geology
  • Volume 26, Issue 1,  2016, pp.23-32
  • Publisher : The Korea Society of Engineering Gelolgy
  • DOI : 10.9720/kseg.2016.1.23
 Title & Authors
Landslide Susceptibility Analysis : SVM Application of Spatial Databases Considering Clay Mineral Index Values Extracted from an ASTER Satellite Image
Nam, Koung-Hoon; Lee, Moung-Jin; Jeong, Gyo-Cheol;
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This study evaluates landslide susceptibility using statistical analysis by SVM (support vector machine) and the illite index of clay minerals extracted from ASTER(advanced spaceborne thermal emission and reflection radiometer) imagery which can be use to create mineralogical mapping. Landslide locations in the study area were identified from aerial photographs and field surveys. A GIS spatial database was compiled containing topographic maps (slope, aspect, curvature, distance to stream, and distance to road), maps of soil properties (thickness, material, topography, and drainage), maps of timber properties (diameter, age, and density), and an ASTER satellite imagery (illite index). The landslide susceptibility map was constructed through factor correlation using SVM to analyze the spatial database. Comparison of area under the curve values showed that using the illite index model provided landslide susceptibility maps that were 76.46% accurate, which compared favorably with 74.09% accuracy achieved without them.
landslide;clay mineral;GIS;ASTER;AUC;
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