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    • A comparative analysis of weight-based machine learning methods for landslide susceptibility mapping in Ha Giang area
    Authors: Trinh, Thanh; Luu, Thanh Binh; Le, Thi Trang Ha; Nguyen, Huy Duong; Tran, Van Trong; Nguyen, Thi Hai Van; Nguyen, Khanh Quoc; Nguyen Thi Lien;  Advisor: -;  Co-Author: - (2022)

    Landslide susceptibility maps (LSMs) are very crucial for planning policies in hazardous areas. However, the accuracy and reliability of LSMs depend on available data and the selection of suitable methods. This study is conducted to produce LSMs by combinations of machine learning methods and weighting techniques for Ha Giang province, Vietnam, where has limited data. In study area, we gather 11 landslide conditioning factors and establish a landslide inventory map. Computing the weights of classes (or factors) is very important to prepare data for machine learning methods to generate LSMs. We first use frequency ratio (FR) and analytic hierarchy process (AHP) techniques to generate t...
    • A comparative analysis of weight-based machine learning methods for landslide susceptibility mapping in Ha Giang area
    Authors: Thanh, Trinh; Binh Thanh, Luu; Trang Ha Thi, Le;  Advisor: -;  Co-Author: - (2022)

    Landslide susceptibility maps (LSMs) are very crucial for planning policies in hazardous areas. However, the accuracy and reliability of LSMs depend on available data and the selection of suitable methods. This study is conducted to produce LSMs by combinations of machine learning methods and weighting techniques for Ha Giang province, Vietnam, where has limited data. In study area, we gather 11 landslide conditioning factors and establish a landslide inventory map. Computing the weights of classes (or factors) is very important to prepare data for machine learning methods to generate LSMs. We first use frequency ratio (FR) and analytic hierarchy process (AHP) techniques to generate t...