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GIS-Based Integration of Subjective and Objective Weighting Methods for Regional Landslides Susceptibility Mapping

Author

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  • Suhua Zhou

    (Department of Geotechnical Engineering, Central South University, Changsha 410075, Hunan, China
    Department of Civil and Structural Engineering, Kyushu University, Fukuoka 819-0395, Japan)

  • Guangqi Chen

    (Department of Civil and Structural Engineering, Kyushu University, Fukuoka 819-0395, Japan)

  • Ligang Fang

    (Department of Geotechnical Engineering, Central South University, Changsha 410075, Hunan, China)

  • Yunwen Nie

    (School of Resource and Environment Science, Hunan Normal University, Changsha 410075, Hunan, China)

Abstract

The development of landslide susceptibility maps is of great importance due to rapid urbanization. The purpose of this study is to present a method to integrate the subjective weight with objective weight for regional landslide susceptibility mapping on the geographical information system (GIS) platform. The analytical hierarchy process (AHP), which is subjective, was employed to weight predictive factors’ contribution to landslide occurrence. The frequency ratio (FR) method, which is objective, was used to derive subclasses’ frequency ratio with respect to landslides that indicate the relative importance of a subclass within each predictive factor. A case study was carried out at Tsushima Island, Japan, using a historical inventory of 534 landslides and seven predictive factors: elevation, slope, aspect, terrain roughness index (TRI), lithology, land cover and mean annual precipitation (MAP). The landslide susceptibility index (LSI) was calculated using the weighted linear combination of factors’ weights and subclasses’ weights. The study area was classified into five susceptibility zones according to the LSI. In addition, the produced susceptibility map was compared with maps generated using the conventional FR and AHP method and validated using the relative landslide index (RLI). The validation result showed that the proposed method performed better than the conventional application of the FR method and AHP method. The obtained landslide susceptibility maps could serve as a scientific basis for urban planning and landslide hazard management.

Suggested Citation

  • Suhua Zhou & Guangqi Chen & Ligang Fang & Yunwen Nie, 2016. "GIS-Based Integration of Subjective and Objective Weighting Methods for Regional Landslides Susceptibility Mapping," Sustainability, MDPI, vol. 8(4), pages 1-15, April.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:4:p:334-:d:67681
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    References listed on IDEAS

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    1. Sung-Ho Kil & Dong Kun Lee & Jun-Hyun Kim & Ming-Han Li & Galen Newman, 2016. "Utilizing the Analytic Hierarchy Process to Establish Weighted Values for Evaluating the Stability of Slope Revegetation based on Hydroseeding Applications in South Korea," Sustainability, MDPI, vol. 8(1), pages 1-17, January.
    2. Qianqian Wang & Dongchuan Wang & Yong Huang & Zhiheng Wang & Lihui Zhang & Qiaozhen Guo & Wei Chen & Wengang Chen & Mengqin Sang, 2015. "Landslide Susceptibility Mapping Based on Selected Optimal Combination of Landslide Predisposing Factors in a Large Catchment," Sustainability, MDPI, vol. 7(12), pages 1-17, December.
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    Cited by:

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    2. Iris Bostjančić & Marina Filipović & Vlatko Gulam & Davor Pollak, 2021. "Regional-Scale Landslide Susceptibility Mapping Using Limited LiDAR-Based Landslide Inventories for Sisak-Moslavina County, Croatia," Sustainability, MDPI, vol. 13(8), pages 1-20, April.
    3. Sangseom Jeong & Azman Kassim & Moonhyun Hong & Nader Saadatkhah, 2018. "Susceptibility Assessments of Landslides in Hulu Kelang Area Using a Geographic Information System-Based Prediction Model," Sustainability, MDPI, vol. 10(8), pages 1-19, August.
    4. Yanyan Li & Jianping Chen & Yanjun Shang, 2016. "An RVM-Based Model for Assessing the Failure Probability of Slopes along the Jinsha River, Close to the Wudongde Dam Site, China," Sustainability, MDPI, vol. 9(1), pages 1-15, December.
    5. Laddyla Bezerra & Osvaldo de Freitas Neto & Olavo Santos & Slobodan Mickovski, 2020. "Landslide Risk Mapping in an Urban Area of the City of Natal, Brazil," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    6. Rui-Xuan Tang & E-Chuan Yan & Tao Wen & Xiao-Meng Yin & Wei Tang, 2021. "Comparison of Logistic Regression, Information Value, and Comprehensive Evaluating Model for Landslide Susceptibility Mapping," Sustainability, MDPI, vol. 13(7), pages 1-25, March.
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