Monitoring and Assessment for the Susceptibility of Landslide Changes After the 2017 Ms 7.0 Jiuzhaigou Earthquake Using the Remote Sensing Technology - Guo, Xinyi; Fu, Bihong; Du, Jie; Shi, Pilong; Li, Jingxia; Li, Zhao; Du, Jiaxin; Chen, Qingyu; Fu, Han (Frontiers in Earth Science, 2021)
Monitoring the change of post-seismic landslides could provide valuable information for geological disaster treatment. The 2017 Jiuzhaigou Ms 7.0 earthquake has triggered a large number of landslides in the Jiuzhaigou United Nations Educational, Scientific and Cultural Organization (UNESCO) Natural Heritage site, which provides a unique opportunity for monitoring the spatio-temporal characteristics and exploring the impact factors of post-seismic landslides change. In this study, the spatio-temporal characteristics of landslides and their post-seismic changes are analyzed using multi-source, multi-temporal, and multi-scale remote sensing data combining with the field study. The Support Vector Machine classification, visual interpretation, field investigation, and Geographic Information System technology are employed to extract landslides and analyze their spatial distribution patterns. Moreover, the Certainty Factor method is used to explore the susceptibility of landslides and to find key impact factors. Our results show that the net increase area of landslide is 1.2 km2 until September 27th, 2019, which are induced by the expansion of coseismic landslide, the post-seismic landslide, and the expansion of vegetation degradation. Moreover, the area expansion of the coseismic and post-seismic landslides is mainly related to the increase of debris flow induced by the post-seismic torrential rainfalls. The highest net increase rate of post-seismic landslide change does not distribute on the regions with the highest density of coseismic landslides. The susceptibility of post-seismic landslide change is greatly influenced by slope, altitude, aspect, peak ground acceleration fault, and strata. It is higher in the coseismic landslide area with low susceptibility. This study also suggests that the potential landslides will most likely occur in the unstable slope region affected by the additional driving force. Therefore, great attention should be paid to identify and prevent the potential landslides on unstable slopes in addition to treatments of the sliding slopes. This study provides a good example for the monitoring and assessment of post-seismic landslides in mountainous regions with a steep slope and deep valley.