Tạp chí
 
Năm 2024
 
Số 65, Kỳ 6, [12 - 2024] - Tiếng Anh

Landslide hazard assessment for the Batxat area of Vietnam using GIS-based spatial prediction models

DOI:10.46326/JMES.2024.65(6).07

  • Cơ quan:

    1 Hanoi University of Mining and Geology, Hanoi, Vietnam
    2 Sergo Ordzhonikidzе Russian State Geological Prospecting University, Moscow, Russia
    3 Vietnam Association of Engineering Geology and Environment, Hanoi, Vietnam
    4 Lomonosov Moscow State University, Moscow, Russia
    5 Institute of Geological Sciences - Vietnam Academy of Science and Technology, Hanoi, Vietnam

  • *Tác giả liên hệ:
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  • Nhận bài: 25-04-2024
  • Sửa xong: 17-08-2024
  • Chấp nhận: 09-09-2024
  • Ngày đăng: 01-12-2024
Trang: 70 - 81
Lượt xem: 32
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Tóm tắt:

Located in the northwest of Laocai province, Batxat district has been frequently affected by natural disasters, including landslides and debris flows. Therefore, landslide hazard assessment (LHA) has been a significant task for planning, economic development, and minimizing human and property damage. For this purpose, landslide hazard maps were established in this study using the Analytic Hierarchy Process (AHP) and the combined Analytic Hierarchy Process - Frequency Ratio (AHP&FR) models. Ten landslide-related factors were selected, including elevation, slope, distance to road, distance to drainage, land use and land cover (LULC), average monthly rainfall, lithology, aspect, distance to fault, and relative relief. Afterwards, the weighted value of landslide-related factors and the landslide susceptibility index (LSI) were determined using the Analytic Hierarchy Process. The Frequency Ratio method was used to calculate the weighted value of factor classes. Two landslide hazard maps were established, and the study area was divided into five hazard zones: very low, low, moderate, high, and very high. The performance of the models was determined using the area under the curve (AUC) of the receiver operating characteristic (ROC), the seed cell area index (SCAI), and the precision of the predicted results (P). The AUC values for the success rate of these models were 0.72 and 0.75, and for the prediction rate were 0.67 and 0.70, respectively. The evaluation results of the models showed that, although both the AHP and combined AHP&FR models have good performance for landslide hazard mapping, the AHP&FR model produces more accurate outcomes than the AHP model.

Trích dẫn
Binh Van Duong, Igor Konstantinovich Fomenko, Ha Viet Nhu, Phuong Huy Nguyen, Olga Nikolaevna Sirotkina, Kien Trung Nguyen và Ha Ngoc Thi Pham, 2024. Landslide hazard assessment for the Batxat area of Vietnam using GIS-based spatial prediction models, Tạp chí Khoa học kỹ thuật Mỏ - Địa chất, số 65, kỳ 6, tr. 70-81.
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