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Evaluation of landslide disaster susceptibility in Shuangbai County based on random forest modeling

Haoyun Xie
International Journal of Computer Science and Information Technology, (2023), Vol.1, No.1, pp.118-123
Published: December 30, 2023
DOI: 10.62051/ijcsit.v1n1.16
PDF: Download Full Text PDF
Abstract

Shuangbai County, Chuxiong Yi Autonomous Prefecture, Yunnan Province, China, has a high incidence of geohazard events and is a key area for geologic risk prevention and control in China, with landslides accounting for the majority of all geohazard events, so understanding landslide-prone areas in the region is critical to reducing the impacts of landslide hazards. In this study, based on literature reference and background investigation of the study area, relevant data and existing research results were collected, and six types of evaluation factors including elevation, slope, slope direction, rainfall, vegetation type and vegetation index were selected to construct a random forest (RF) model to analyze the landslide susceptibility of Shuangbai County, Chuxiong Prefecture, Yunnan Province, and to obtain the evaluation map of landslide susceptibility in Shuangbai County. The results show that the landslide disaster high susceptibility areas in Shuangbai County are mainly distributed in the northern part of the county in Toudian Township and Dazhuang Township, the southeastern part of Anlongbao Township and the southwestern part of Ejia Township in the vicinity of the Hengduan Mountain Range, which is an important reference for the development of scientific and effective disaster prevention and mitigation strategies, and for the enhancement of the quality of life and the safety of the residents in the area of Shuangbai County.

Keywords: landslides, Random forest, Susceptibility assessment
APA Citation: Haoyun Xie (2023). Evaluation of landslide disaster susceptibility in Shuangbai County based on random forest modeling. International Journal of Computer Science and Information Technology, 1(1), 118-123. https://doi.org/10.62051/ijcsit.v1n1.16

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