Landslide Hazard Assessment in Minjiang River Basin Based on GIS and Random Forest Algorithm

被引:0
作者
Cheng, Yashan [1 ]
Chen, Qiuhe [1 ]
Yu, Yingzhuo [2 ]
Xia, Yuling [1 ]
机构
[1] Officers Coll PAP, Dept Informat & Commun, Chengdu 610000, Sichuan, Peoples R China
[2] Nanjing Inst Environm Sci, Minist Ecol & Environm, Nanjing 210000, Jiangsu, Peoples R China
来源
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ALGORITHMS, SOFTWARE ENGINEERING, AND NETWORK SECURITY, ASENS 2024 | 2024年
关键词
Minjiang River Basin; landslide; hazard evaluation; GIS; Random Forest Algorithm; CHINA;
D O I
10.1145/3677182.3677227
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Disaster risk assessment is an effective tool for landslide disaster management. Machine learning models can effectively avoid the subjectivity of determining the weights of factors in disaster risk assessment, which is a hotspot of current research. We evaluate the risk of landslide disaster in Minjiang River Basin by Random Forest Algorithm based on characters include rainfall, slope, vegetation cover, distance to river and distance to fault. The results show that landslides in the Minjiang River Basin are closely related to the distance to the river and the distance to the faults. About 11.5% of the total area of the Minjiang River Basin is susceptible to small landslides.
引用
收藏
页码:249 / 253
页数:5
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