AUTHOR=Liu Xuemei , Yang Xianhe , Yuan Renmao , Xu Rui , Liu Chaohai TITLE=Seismic landslide susceptibility evaluation model based on historical data and its application to areas with similar environmental settings JOURNAL=Frontiers in Earth Science VOLUME=12 YEAR=2024 URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2024.1419851 DOI=10.3389/feart.2024.1419851 ISSN=2296-6463 ABSTRACT=

Seismic landslide susceptibility evaluation models are usually built on the basis of historical sample data; however, the evaluation results are often unsatisfactory when the environmental settings differ between the historical sample data region and application region. Therefore, similarity between the environmental settings is important for the application of such models. In this paper, a seismic landslide susceptibility evaluation model was first built using data from the 2008 Ms 8.0 Wenchuan earthquake-induced landslide, and the model was then used to evaluate the 2022 Ms 6.8 Luding earthquake area. In addition, the grade of susceptibility is typically represented by the landslide density, which is insufficient for capturing the details of landslides, such as their sizes, frequencies, and spatial distribution patterns. The authors therefore use a large and concentrated landslide as the susceptibility grade for the Luding earthquake area. The test results demonstrate that these two areas have similar background environments. The area under the curve (AUC) value of the receiver operating characteristics (ROC) curve of the evaluation accuracy for the model applied to the Luding earthquake area is 0.889, which indicates relatively high accuracy. Besides, the results also demonstrate that the evaluations are consistent with the disaster situation of the Moxi Platform, Wandong Village, as well as the Dagangshan Hydropower Station area. Therefore, it is reliable to apply the susceptibility evaluation model based on the Wenchuan earthquake data to the Luding earthquake area. These results show that better evaluations can be obtained based on environmental similarity tests between the areas used for historical data modeling and areas to which the models are applied.