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 AN ASSESSMENT OF TERRAIN QUALITY AND SELECTION MODEL IN DEVELOPING LANDSLIDE SUSCEPTIBILITY MAP – A CASE STUDY IN MOUNTAINOUS AREAS OF QUANG NGAI PROVINCE, VIETNAM
Tác giả hoặc Nhóm tác giả: Doan Viet Long, Nguyen Chi Cong, Nguyen Tien Cuong, Nguyen Quang Binh, Vo Nguyen Duc Phuoc
Nơi đăng: THE INTERNATIONAL CONFERENCE ON MODERN MECHANICS AND APPLICATIONS ICOMMA 2020; Số: https://doi.org/10.1007/978-981-16-3239-6_75;Từ->đến trang: 1-12;Năm: 2021
Lĩnh vực: Khoa học công nghệ; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
Landslide is one of the most common natural disasters in mountainous area of Vietnam. Therefore, studying and developing a landslide susceptibility map would make a significant contribution to local authorities in taking initiative in landslide prevention and mitigation. The quality of input data and the choice of model building methods are two very important impacted factors to accuracy of produced maps. This study will focus on investigating the influences of terrain data, which is a significant causative factor on landslides, to select the most appropriate DEM model. The DEM will be combined with other impact factors to develop landslide susceptibility assessment by applying two landslide spatial analysis methods: Analytic Hierarchy Process (AHP) and Frequency Ratio (FR). Conducting the investigation with three free sources of Digital Elevation Models (DEMs) in mountainous areas of Quang Ngai province has shown that NasaDEM performs better than the other DEMs (TanDEM-X90 and STRM). For this purpose, a total of 339 landslide locations was collected in this area, and then randomly split into two parts to generate training (70%) and testing (30%) datasets for construction and validation of the map, respectively. In addition, seven affecting factors were selected, including slope, aspect, soil types, land use, distance to roads, distance to rivers, and rainfall for developing the models. Validation of the maps was done using two performances indexes namely Untainted Area Under the Curve (AUC) and Landslide Density (LD). The results show that that two methods are appropriate for producing landslide susceptibility maps. Meanwhile, analyzing using the FR would get better AUC (0.793 > 0.747) and LD index compared to the AHP.
ABSTRACT
Landslide is one of the most common natural disasters in mountainous area of Vietnam. Therefore, studying and developing a landslide susceptibility map would make a significant contribution to local authorities in taking initiative in landslide prevention and mitigation. The quality of input data and the choice of model building methods are two very important impacted factors to accuracy of produced maps. This study will focus on investigating the influences of terrain data, which is a significant causative factor on landslides, to select the most appropriate DEM model. The DEM will be combined with other impact factors to develop landslide susceptibility assessment by applying two landslide spatial analysis methods: Analytic Hierarchy Process (AHP) and Frequency Ratio (FR). Conducting the investigation with three free sources of Digital Elevation Models (DEMs) in mountainous areas of Quang Ngai province has shown that NasaDEM performs better than the other DEMs (TanDEM-X90 and STRM). For this purpose, a total of 339 landslide locations was collected in this area, and then randomly split into two parts to generate training (70%) and testing (30%) datasets for construction and validation of the map, respectively. In addition, seven affecting factors were selected, including slope, aspect, soil types, land use, distance to roads, distance to rivers, and rainfall for developing the models. Validation of the maps was done using two performances indexes namely Untainted Area Under the Curve (AUC) and Landslide Density (LD). The results show that that two methods are appropriate for producing landslide susceptibility maps. Meanwhile, analyzing using the FR would get better AUC (0.793 > 0.747) and LD index compared to the AHP.
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