Spatial distribution patterns and hazard assessment of co-seismic landslides triggered by the 2022 Luding earthquake (MS 6.8): An RF-AdaBoost model approach

IF 5.1 3区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY
China Geology Pub Date : 2026-04-01 Epub Date: 2026-05-22 DOI:10.31035/cg2024117
Li-ying Gu , Guo-liang Du , Ling Zou , Xin Wang
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Abstract

On September 5, 2022, a magnitude 6.8 earthquake struck Luding County, Sichuan Province, China, at a depth of 16 km, triggering numerous co-seismic landslides. Using multi-temporal satellite imagery, the authors identified 7463 co-seismic landslides with varying spatial distributions. Focusing on the differences between the western and eastern sections of the Xianshuihe fault zone, the influences of elevation, slope, aspect, topographic wetness index (TWI), stream power index (SPI), distance to river, distance to seismogenic fault, seismic intensity, lithology, and land surface temperature (LST) on the co-seismic landslide distribution were analyzed. Random Forest-Adaptive Boosting (RF-AdaBoost), Support Vector Machine (SVM) and Back Propagation Neural Network (BP) models were used to assess landslide hazards in the region. The RF-AdaBoost model performed the best, achieving an Area Under the Curve (AUC) of 0.954. The zones of high co-seismic landslide hazard were primarily concentrated along the Xianshuihe fault zone and Dadu River. These findings provide valuable insights into seismic landslide hazard assessments and offer scientific guidance for disaster prevention and mitigation strategies.
基于RF-AdaBoost模型的2022年泸定6.8级地震诱发同震滑坡空间分布格局及危险性评价
2022年9月5日,中国四川省泸定县发生6.8级地震,震源深度16公里,引发多处同震滑坡。利用多时相卫星图像,作者确定了7463个具有不同空间分布的同震滑坡。针对鲜水河断裂带东西段的差异,分析了高程、坡度、坡向、地形湿度指数(TWI)、水流功率指数(SPI)、距河流距离、距发震断层距离、地震烈度、岩性、地表温度(LST)等因素对同震滑坡分布的影响。采用随机森林自适应增强(RF-AdaBoost)、支持向量机(SVM)和反向传播神经网络(BP)模型对该地区的滑坡危险性进行了评估。RF-AdaBoost模型表现最佳,曲线下面积(AUC)为0.954。同震滑坡高发区主要集中在鲜水河断裂带和大渡河沿线。这些发现为地震滑坡危险性评估提供了有价值的见解,并为防灾减灾战略提供了科学指导。
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来源期刊
China Geology
China Geology GEOLOGY-
CiteScore
7.80
自引率
11.10%
发文量
275
审稿时长
16 weeks
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