Hazard Assessment of Rainfall–Induced Landslide Considering the Synergistic Effect of Natural Factors and Human Activities

Qing Lan, Jianbo Tang, Xiaoming Mei, Xuexi Yang, Qinghao Liu () and Qian Xu
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Qing Lan: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Jianbo Tang: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Xiaoming Mei: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Xuexi Yang: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Qinghao Liu: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Qian Xu: School of Geosciences and Info-Physics, Central South University, Changsha 410083, China

Sustainability, 2023, vol. 15, issue 9, 1-19

Abstract: Landslide hazard assessment is essential for determining the probability of landslide occurrence in a specific spatial and temporal range. The hazard assessment of potential landslides could support landslide disaster early warning and disaster prevention decisions, which have important guiding significance for urban construction and sustainable development. Due to the lack of consideration of the synergistic effect of multiple factors and geographic scene heterogeneity, the accuracy of existing landslide hazard assessment methods still needs to be improved, and the interpretability and applicability of existing models still need to be improved. In this paper, we propose a landslide hazard assessment method considering the synergistic effect of multiple factors, including natural factors and human activities, and the heterogeneity of geographic scenes. On this basis, we carry out experimental verification on rainfall–induced landslides in Dehong Prefecture, Yunnan Province, China. Firstly, rainfall–induced landslide hazards’ characteristics and impact factors are analyzed and classified. The whole study area is divided into some homogeneous sub–regions using regional dynamic constraint clustering based on the similarity of underlying environmental variables. Then, considering the spatial autocorrelation between various landslide conditioning and trigger factors, a local weighted random forest model is developed to evaluate the rainfall–induced landslide hazards comprehensively. Experimental results show that the proposed method has higher accuracy and interpretability than the existing representative methods and can provide useful references for preventing landslide hazards.

Keywords: rainfall–induced landslides; hazard assessment; multiple factors; heterogeneity; Dehong prefecture (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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