Abstract
Rapid and effective evaluation of landslide susceptibility after earthquakes is critical for various applications, such as emergency rescue, land planning, and disaster prevention. Current research suffers from the lack of a complete landslide inventory and sample selection uncertainty issues. To solve these problems, this study presents a landslide susceptibility mapping model that integrates one-class support vector machine (OCSVM) and an incomplete landslide inventory, which was established with the aid of change detection from bi-temporal Landsat images. Wenchuan County is selected as the study area to test the performance of the proposed method. The proposed method is also compared with standard two-class SVM that selects a sample randomly. Experimental results show that OCSVM can achieve better performance than SVM when only an incomplete landslide inventory is available. The findings of this study can be applied to determine regional landslide susceptibility after earthquakes and provide an essential reference for emergency response.
Highlights
O N May 12, 2008, a MS 8.0 earthquake occurred in Wenchuan county, Sichuan province, which triggered a large number of landslide, causing great economic losses and casualties [1]
According to the incomplete landslide inventory obtained for the study area, the Wenchuan earthquake triggered a 170.49 km2 seismic landslide in the scope of 4138 km2
The seismic landslide was affected by ground motion, resulting in a seismic landslide characterized by long-distance ejection [44]; the influence scope of the landslide was not limited to a single SU [45]
Summary
O N May 12, 2008, a MS 8.0 earthquake occurred in Wenchuan county, Sichuan province, which triggered a large number of landslide, causing great economic losses and casualties [1]. In the process of post-earthquake emergency rescue, it is necessary to quickly locate the high-risk area of seismic landslide, so as to provide a basis for seeking the best rescue opportunity and optimizing emergency rescue deployment. Timely evaluation of landslide susceptibility after an earthquake is critical to various applications, such as emergency rescue and disaster prevention [2]
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