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A Comparative Analysis of Landslide Susceptibility Assessment by Using Global and Spatial Regression Methods in Inje Area, Korea
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 Title & Authors
A Comparative Analysis of Landslide Susceptibility Assessment by Using Global and Spatial Regression Methods in Inje Area, Korea
Park, Soyoung; Kim, Jinsoo;
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 Abstract
Landslides are major natural geological hazards that result in a large amount of property damage each year, with both direct and indirect costs. Many researchers have produced landslide susceptibility maps using various techniques over the last few decades. This paper presents the landslide susceptibility results from the geographically weighted regression model using remote sensing and geographic information system data for landslide susceptibility in the Inje area of South Korea. Landslide locations were identified from aerial photographs. The eleven landslide-related factors were calculated and extracted from the spatial database and used to analyze landslide susceptibility. Compared with the global logistic regression model, the Akaike Information Criteria was improved by 109.12, the adjusted R-squared was improved from 0.165 to 0.304, and the Moran’s I index of this analysis was improved from 0.4258 to 0.0553. The comparisons of susceptibility obtained from the models show that geographically weighted regression has higher predictive performance.
 Keywords
Landslide;Landslide Susceptibility Map;Geographically Weighted Regression;Logistic Regression Model;
 Language
English
 Cited by
1.
Spatial prediction of rotational landslide using geographically weighted regression, logistic regression, and support vector machine models in Xing Guo area (China), Geomatics, Natural Hazards and Risk, 2017, 8, 2, 1997  crossref(new windwow)
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