Extraction of landslide-related factors from ASTER imagery and its application to landslide susceptibility mapping

被引:28
|
作者
Oh, Hyun-Joo [3 ]
Park, No-Wook [2 ]
Lee, Sung-Soon [1 ]
Lee, Saro [1 ]
机构
[1] Korea Inst Geosci & Mineral Resources, Geosci Informat Ctr, Taejon 305350, South Korea
[2] Inha Univ, Dept Geoinformat Engn, Inchon 402751, South Korea
[3] Korea Inst Geosci & Mineral Resources, Dept Oversea Mineral Resources, Taejon 305350, South Korea
关键词
ARTIFICIAL NEURAL-NETWORK; REMOTE-SENSING DATA; 3 GORGES AREA; LOGISTIC-REGRESSION; CONDITIONAL-PROBABILITY; LANTAU ISLAND; GIS; MODEL; VALIDATION; ACCURACY;
D O I
10.1080/01431161.2010.545084
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
The aim of this study is to extract landslide-related factors from remote-sensing data, such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery, and to examine their applicability to landslide susceptibility near Boun, Korea, using a geographic information system (GIS). Landslide was mapped from interpretation of aerial photographs and field surveying. Factors that influence landslide occurrence were extracted from ASTER imagery. The slope, aspect and curvature were calculated from the digital elevation model (DEM) with 25.77 m root mean square error (RMSE), which was derived from ASTER imagery. Lineaments, land-cover and normalized difference vegetation index (NDVI) layers were also estimated from ASTER imagery. Landslide-susceptible areas were analysed and mapped using the occurrence factors by a frequency ratio and logistic regression model. Validation results were 84.78% in frequency ratio and 84.20% in logistic regression prediction accuracy for the susceptibility map with respect to ground-truth data.
引用
收藏
页码:3211 / 3231
页数:21
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