Evaluation of landslide susceptibility based on VW-AHP-IV model: a case of Pengyang County, Ningxia, China

被引:3
|
作者
Li, Minghong [1 ]
Qiu, Yang [1 ]
Xiong, Hanxiang [1 ]
Zhang, Zechen [2 ]
机构
[1] China Univ Geosci, Sch Environm Studies, Wuhan 430074, Peoples R China
[2] China Univ Geosci, Sch Geol Survey, Wuhan 430074, Peoples R China
关键词
Landslide susceptibility; VW-AHP-IV model; State level; Information value; Prevention and control; LOGISTIC-REGRESSION; FREQUENCY RATIO; GIS; HAZARD;
D O I
10.1007/s12665-023-10787-5
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Landslide is one of the most common and severe geological disasters, which significantly endangers people's lives and properties. Therefore, adequate evaluation of landslide susceptibility is an important for disaster control and mitigation. We selected Pengyang County as the study area, and divided the indicators into different state levels by graded area ratio and landslide occurrence frequency distribution. Meanwhile, the levels of each indicator were assigned the unique scores according to the corresponding information values. Given that the issue of subjectivity in single AHP model significantly influence the model performance in landslide susceptibility prediction, a hybrid model, namely variable-weight based weighted information value (VW-AHP-IV) model, was applied in this paper for landslide susceptibility evaluation. The study area was classified into five classes by the natural breakpoint method: very high susceptibility area (8.26%), high susceptibility area (19.78%), medium susceptibility area (29.93%), low susceptibility area (31.57%) and very low susceptibility area (10.46%). In addition, this paper also discussed the influences of precipitation and human activities on landslide occurrence. According to the evaluation results and discussion, the study area was classified into three prevention and control areas: focus prevention and control area, sub-focus prevention and control area, and general prevention and control area. For each area, the corresponding prevention and control suggestions were proposed in order to reduce the occurrence of landslide disasters.
引用
收藏
页数:20
相关论文
共 50 条
  • [41] Accuracy Improvement of Different Landslide Susceptibility Evaluation Models through K -Means Clustering: A Case Study on China's Funing County
    Wu, Yu-Feng
    Fa-You, A.
    Yang, Cheng
    Yan, Shi-Qun
    Kang, Xiao-Bo
    Mathematical Problems in Engineering, 2023, 2023
  • [42] GIS-based Landslide Susceptibility Evaluation Using Analytical Hierarchy Process (AHP) Approach: The Case of Tarmaber District, Ethiopia
    Abay, Asmelash
    Barbieri, Giulio
    Woldearegay, Kifle
    MOMONA ETHIOPIAN JOURNAL OF SCIENCE, 2019, 11 (01): : 14 - 36
  • [43] Application of analytic hierarchy process model for landslide susceptibility mapping in the Gangu County, Gansu Province, China
    Wu, Yanli
    Li, Wenping
    Liu, Ping
    Bai, Hanying
    Wang, Qiqing
    He, Jianghui
    Liu, Yu
    Sun, Shangshang
    ENVIRONMENTAL EARTH SCIENCES, 2016, 75 (05) : 1 - 11
  • [44] Application of analytic hierarchy process model for landslide susceptibility mapping in the Gangu County, Gansu Province, China
    Yanli Wu
    Wenping Li
    Ping Liu
    Hanying Bai
    Qiqing Wang
    Jianghui He
    Yu Liu
    Shangshang Sun
    Environmental Earth Sciences, 2016, 75
  • [45] Study on Landslide Susceptibility Based on Multi-Model Coupling: A Case Study of Sichuan Province, China
    Zhang, Jinming
    Qian, Jianxi
    Lu, Yuefeng
    Li, Xueyuan
    Song, Zhenqi
    SUSTAINABILITY, 2024, 16 (16)
  • [46] A side-sampling based Linformer model for landslide susceptibility assessment: a case study of the railways in China
    Jiang, Nan
    Li, Yange
    Han, Zheng
    Yang, Jiaming
    Fu, Bangjie
    Li, Jiaying
    Li, Changli
    GEOMATICS NATURAL HAZARDS & RISK, 2024, 15 (01)
  • [47] Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China)
    Wang, Yue
    Sun, Deliang
    Wen, Haijia
    Zhang, Hong
    Zhang, Fengtai
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (12) : 1 - 39
  • [48] Evaluation of Landslide Susceptibility Based on GIS and WOE-BP Model
    Guo Z.
    Yin K.
    Fu S.
    Huang F.
    Gui L.
    Xia H.
    Diqiu Kexue - Zhongguo Dizhi Daxue Xuebao/Earth Science - Journal of China University of Geosciences, 2019, 44 (12): : 4299 - 4312
  • [49] Evaluation of landslide susceptibility based on information volume and neural network model
    Chen F.
    Cai C.
    Li X.
    Suntao
    Qian Q.
    Yanshilixue Yu Gongcheng Xuebao/Chinese Journal of Rock Mechanics and Engineering, 2020, 39 : 2859 - 2870
  • [50] Ensemble stacking: a powerful tool for landslide susceptibility assessment - a case study in Anhua County, Hunan Province, China
    Liu, Lei-Lei
    Danish, Aasim
    Wang, Xiao-Mi
    Zhu, Wen-Qing
    GEOCARTO INTERNATIONAL, 2024, 39 (01)