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Susceptibility Assessments of Landslides in Hulu Kelang Area Using a Geographic Information System-Based Prediction Model

Author

Listed:
  • Sangseom Jeong

    (School of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

  • Azman Kassim

    (Department of Geotechnics and Transportation, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia)

  • Moonhyun Hong

    (School of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

  • Nader Saadatkhah

    (Department of Civil Engineering, Faculty of Engineering, Islamic Azad University (IAU), Kerman Branch, Kerman 761, Iran)

Abstract

This study was conducted to estimate the susceptibility of landslides on a test site in Malaysia (Hulu Kelang area). A Geographic Information system (GIS)-based physical model named YS-Slope, which integrates a mechanistic infinite slope stability method and the geo-hydrological model was applied to calculate the safety factor of the test site. Input data, slopes, soil-depth, elevations, soil properties and plant covers were constructed as GIS datasets. The factor of safety of shallow landslides along the wetting front and deep-seated landslides at the bottom of the groundwater were estimated to compare with the analysis results of the existing model and actual landslides in 2008. According to the results of the study, shallow landslides mainly occurred in the central area which has many historical landslides, while deep-seated landslides were predominant in the east side of the study area. A ROC analysis was conducted and it is shown that the prediction result at the end of the northeast monsoon for shallow landslides showed relatively high accuracy compared with other predictions.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:8:p:2941-:d:164520
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    References listed on IDEAS

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    1. Sangseom Jeong & Kwangwoo Lee & Junghwan Kim & Yongmin Kim, 2017. "Analysis of Rainfall-Induced Landslide on Unsaturated Soil Slopes," Sustainability, MDPI, vol. 9(7), pages 1-20, July.
    2. 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.
    3. Ho Gul Kim & Dong Kun Lee & Chan Park, 2018. "Assessing the Cost of Damage and Effect of Adaptation to Landslides Considering Climate Change," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
    4. Min Lee & Kim Ng & Yuk Huang & Wei Li, 2014. "Rainfall-induced landslides in Hulu Kelang area, Malaysia," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(1), pages 353-375, January.
    5. Yongmin Kim & Hyundo Park & Sangseom Jeong, 2017. "Settlement Behavior of Shallow Foundations in Unsaturated Soils under Rainfall," Sustainability, MDPI, vol. 9(8), pages 1-13, August.
    6. 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:

    1. Yigen Qin & Genlan Yang & Kunpeng Lu & Qianzheng Sun & Jin Xie & Yunwu Wu, 2021. "Performance Evaluation of Five GIS-Based Models for Landslide Susceptibility Prediction and Mapping: A Case Study of Kaiyang County, China," Sustainability, MDPI, vol. 13(11), pages 1-20, June.
    2. Paul Sestraș & Ștefan Bilașco & Sanda Roșca & Sanda Naș & Mircea V. Bondrea & Raluca Gâlgău & Ioel Vereș & Tudor Sălăgean & Velibor Spalević & Sorin M. Cîmpeanu, 2019. "Landslides Susceptibility Assessment Based on GIS Statistical Bivariate Analysis in the Hills Surrounding a Metropolitan Area," Sustainability, MDPI, vol. 11(5), pages 1-23, March.
    3. Siti Norsakinah Selamat & Nuriah Abd Majid & Mohd Raihan Taha & Ashraf Osman, 2022. "Landslide Susceptibility Model Using Artificial Neural Network (ANN) Approach in Langat River Basin, Selangor, Malaysia," Land, MDPI, vol. 11(6), pages 1-21, June.

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