Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis |
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Authors: | No-Wook Park |
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Institution: | (1) Department of Geoinformatic Engineering, Inha University, 253 Yonghyun-dong, Nam-gu, Incheon, 402-751, Korea |
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Abstract: | GIS-based spatial data integration tasks for predictive geological applications, such as landslide susceptibility analysis,
have been regarded as one of the primary geological application issues of GIS. An efficient framework for proper representation
and integration is required for this kind of application. This paper presents a data integration framework based on the Dempster-Shafer
theory of evidence for landslide susceptibility mapping with multiple geospatial data. A data-driven information representation
approach based on spatial association between known landslide occurrences and input geospatial data layers is used to assign
mass functions. After defining mass functions for multiple geospatial data layers, Dempster’s rule of combination is applied
to obtain a series of combined mass functions. Landslide susceptibility mapping using multiple geospatial data sets from Jangheung
in Korea was conducted to illustrate the application of this methodology. The results of the case study indicated that the
proposed methodology efficiently represented and integrated multiple data sets and showed better prediction capability than
that of a traditional logistic regression model. |
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Keywords: | |
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