Susceptibility Assessment of Landslides in Alpine-Canyon Region Using Multiple GIS-Based Models

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Date: June 2019
Publisher: Springer
Document Type: Report
Length: 291 words

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Byline: Man Hu (1), Qiuqiang Liu (2), Pengyu Liu (1) Keywords: landslide; susceptibility assessment; geographic information system (GIS); analytical hierarchy process (AHP); fuzzy logic (FL); certainty factors (CF); TP 305 Abstract: This study explores a comparative study of three susceptibility assessment models based on remote sensing (RS) and geographic information system (GIS). The Lenggu region (China) was selected as a case study. At first, a landslide inventory map was compiled using data from existing geology reports, satellite imagery, and coupling with field observations. Subsequently, three models were built to map the landslide susceptibility using analytical hierarchy process (AHP), fuzzy logic (FL) and certainty factors (CF). The resulting models were validated and compared using areas under the curve (AUC). The AUC plot estimation results indicated that the three models are promising methods for landslide susceptibility mapping. Among the three methods, CF model has highest prediction accuracy than the other two models. Similarly, the outcome of this study reveals that streams, faults, slope and elevation are the main conditioning factors of landslides. Especially, the erosion of streams plays a key role of the landslide occurrence. These landslide susceptibility maps, to some extent, reflect spatial distribution characteristics of landslides in alpine- canyon region of southwest China, and can be used for land planning and hazard risk assessment. Author Affiliation: (1) grid.263906.8, College of Engineering and Technology, Southwest University, Chongqing, 400715, China (2) grid.453137.7, Consultative Centre for Geo-Hazard Emergency, Ministry of Land and Resources of China, Beijing, 100081, China Article History: Registration Date: 13/05/2019 Received Date: 28/07/2018 Online Date: 14/05/2019 Article note: Foundation item: Supported by the National Natural Science Foundation of China (41602354), the Chongqing Research Program of Basic Research and Frontier Technology (2017jcyjAX0300), and the Fundamental Research Funds for the Central Universities (XDJK2016B027)

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Gale Document Number: GALE|A585460352