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
相关论文
共 50 条
  • [1] GIS-Based Spatial Analysis and Modeling for Landslide Hazard Assessment:A Case Study in Upper Minjiang River Basin
    FENG Wenlan 1
    2. Graduate University of Chinese Academy of Sciences
    3. Department of Envioronmental Engineering
    WuhanUniversityJournalofNaturalSciences, 2006, (04) : 847 - 852
  • [2] Landslide Susceptibility Mapping and Interpretation in the Upper Minjiang River Basin
    Wang, Xin
    Bai, Shibiao
    REMOTE SENSING, 2023, 15 (20)
  • [3] GIS-based landslide hazard assessment: an overview
    Wang, HB
    Liu, GJ
    Xu, WY
    Wang, GH
    PROGRESS IN PHYSICAL GEOGRAPHY-EARTH AND ENVIRONMENT, 2005, 29 (04): : 548 - 567
  • [4] Regional Color Study of Traditional Village Based on Random Forest Model: Taking the Minjiang River Basin as an Example
    Kong, Deyi
    Fei, Xinhui
    Lu, Zexuan
    Lin, Xinyue
    Cai, Mengqing
    Chen, Zujian
    BUILDINGS, 2025, 15 (04)
  • [5] A Novel GIS-Based Random Forest Machine Algorithm for the Spatial Prediction of Shallow Landslide Susceptibility
    Viet-Hung Dang
    Nhat-Duc Hoang
    Le-Mai-Duyen Nguyen
    Dieu Tien Bui
    Samui, Pijush
    FORESTS, 2020, 11 (01):
  • [6] Landslide Hazard Zonation using Remote Sensing and GIS: a case study of Dikrong river basin, Arunachal Pradesh, India
    Pandey, Ashish
    Dabral, P. P.
    Chowdary, V. M.
    Yadav, N. K.
    ENVIRONMENTAL GEOLOGY, 2008, 54 (07): : 1517 - 1529
  • [7] A GIS-based landslide hazard assessment by multiple regression analysis
    Pan, Xiaoduo
    Nakamura, Hiroyuki
    Tamotsu, Nozaki
    Nan, Zhuotong
    GEOINFORMATICS 2007: GEOSPATIAL INFORMATION TECHNOLOGY AND APPLICATIONS, PTS 1 AND 2, 2007, 6754
  • [8] Landslide hazard mapping of Ibrahim River Basin, Lebanon
    Abdallah, C.
    Faour, G.
    NATURAL HAZARDS, 2017, 85 (01) : 237 - 266
  • [9] Landslide hazard mapping of Ibrahim River Basin, Lebanon
    C. Abdallah
    G. Faour
    Natural Hazards, 2017, 85 : 237 - 266
  • [10] Probabilistic landslide hazard assessment at the basin scale
    Guzzetti, F
    Reichenbach, P
    Cardinali, M
    Galli, M
    Ardizzone, F
    GEOMORPHOLOGY, 2005, 72 (1-4) : 272 - 299