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 Predicting Landslide Spatial Probability in Quang Ngai, Vietnam using Deep Learning Technique
Tác giả hoặc Nhóm tác giả: V. Nguyen Ba Quang, L. Doan Viet, C. Nguyen Chi, P. Vo Nguyen Duc and B. Nguyen Quang
Nơi đăng: EarthDoc (Scopus); Số: 4th Asia Pacific Meeting on Near Surface Geoscience & Engineering;Từ->đến trang: 1-5;Năm: 2022
Lĩnh vực: Kỹ thuật; Loại: Bài báo khoa học; Thể loại: Quốc tế
TÓM TẮT
ABSTRACT
Rainfall is one of a natural triggering factor for landslides. Vietnam, with � area covered by mountainous area, is located in one of five major typhoon areas in the world. Therefore, rainfall-triggered landslides are a constant threat to life, agriculture and transport in Vietnam. So, predicting landslide spatial probability in Vietnam is an urgent requirement. In this study, a deep learning model was used to assess landslide spatial probability at Quang Ngai province, Vietnam. 650 landslides along with 12 conditioning factors were used in landslide spatial probability mapping. The results were validated using a receiver operating characteristic curves. The areas under the curve of the success-rate curve and predicted-rate curve showed that the proposed model was successful in predicting the spatial probability of landslide at Quang Ngai, Vietnam. In addition, the used model was compared to other machine learning models and showed better performance than the other models. A classified landslide susceptibility maps were established from the landslide spatial probability map by different classifiers. Statistical tests were also performed and indicated that the classified landslide susceptibility map had statistical significance.
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