Articles | Volume 16, issue 17
Model evaluation paper
06 Sep 2023
Model evaluation paper |  | 06 Sep 2023

Hazard assessment modeling and software development of earthquake-triggered landslides in the Sichuan–Yunnan area, China

Xiaoyi Shao, Siyuan Ma, and Chong Xu

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Cited articles

Allstadt, K. E., Jibson, R. W., Thompson, E. M., Massey, C. I., Wald, D. J., Godt, J. W., and Rengers, F. K.: Improving near-real-time coseismic landslide models: Lessons learned from the 2016 Kaikōura, New Zealand, Earthquake, B. Seismol. Soc. Am., 108, 1649–1664,, 2018. 
Bai, S. B., Lu, P., and Wang, J.: Landslide susceptibility assessment of the Youfang Catchment using logistic regression, J. Mt. Sci., 816–827,, 2015. 
Bragagnolo, L., da Silva, R. V., and Grzybowski, J. M. V.: Landslide susceptibility mapping with r.landslide: A free open-source GIS-integrated tool based on Artificial Neural Networks, Environ. Modell. Softw., 123, 104565,, 2020. 
Brenning, A.: Spatial prediction models for landslide hazards: review, comparison and evaluation, Nat. Hazards Earth Syst. Sci., 5, 853–862,, 2005. 
Broeckx, J., Vanmaercke, M., Duchateau, R., and Poesen, J.: A data-based landslide susceptibility map of Africa, Earth-Sci. Rev., 185, 102–121,, 2018. 
Short summary
Scientific understandings of the distribution of coseismic landslides, followed by emergency and medium- and long-term risk assessment, can reduce landslide risk. The aim of this study is to propose an improved three-stage spatial prediction strategy and develop corresponding hazard assessment software called Mat.LShazard V1.0, which provides a new application tool for coseismic landslide disaster prevention and mitigation in different stages.