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Landslide Susceptibility Assessment Using the Analytic Hierarchy Process (AHP): A Case Study of a Construction Site for Photovoltaic Power Generation in Yunxian County, Southwest China

Author

Listed:
  • Jinxuan Zhou

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China)

  • Shucheng Tan

    (School of Earth Sciences, Yunnan University, Kunming 650500, China)

  • Jun Li

    (Yunnan Architecture Engineering Design Company Limited, Kunming 650501, China)

  • Jian Xu

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China)

  • Chao Wang

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China)

  • Hui Ye

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China)

Abstract

China is actively promoting the construction of clean energy to reach its objective of achieving carbon neutrality. However, engineering constructions in mountainous regions are susceptible to landslide disasters. Therefore, the assessment of landslide disaster susceptibility is indispensable for disaster prevention and risk management in construction projects. In this context, the present study involved conducting a field survey at 42 landslide points in the selected planned site region. According to the geological and geographical conditions of the study region, the existing regulation, and the influencing factors of landslides, the assessment in the field survey was performed based on 11 impact factors, namely, the slope, slope aspect, curvature, relative relief, NDVI, road, river, fault, lithology, the density of the landslide points, and the land-use type. Next, based on their respective influences, these impact factors were further divided into subfactors according to AHP, and the weights of each factor and subfactor were calculated. The GIS tools were employed for linear combination calculation and interval division, and accordingly, a landslide susceptibility zone map was constructed. The ROC curve was adopted to test the partition evaluation results, and the AUC value was determined to be 0.845, which indicated the high accuracy of the partition evaluation results.

Suggested Citation

  • Jinxuan Zhou & Shucheng Tan & Jun Li & Jian Xu & Chao Wang & Hui Ye, 2023. "Landslide Susceptibility Assessment Using the Analytic Hierarchy Process (AHP): A Case Study of a Construction Site for Photovoltaic Power Generation in Yunxian County, Southwest China," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5281-:d:1099087
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    Citations

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    Cited by:

    1. Peng Yu & Jie Dong & Hongwei Hao & Yongjian Xie & Hui Zhang & Jianshou Wang & Chenghao Zhu & Yong Guan & Haochen Yu, 2023. "Risk Assessment and Prevention Planning for Collapse Geological Hazards Considering Extreme Rainfall—A Case Study of Laoshan District in Eastern China," Land, MDPI, vol. 12(8), pages 1-22, August.
    2. Huan Lin & Xiaolei Deng & Jianping Yu & Xiaoliang Jiang & Dongsong Zhang, 2023. "A Study of Sustainable Product Design Evaluation Based on the Analytic Hierarchy Process and Deep Residual Networks," Sustainability, MDPI, vol. 15(19), pages 1-22, October.
    3. Shaohan Zhang & Shucheng Tan & Jinxuan Zhou & Yongqi Sun & Duanyu Ding & Jun Li, 2023. "Geological Disaster Susceptibility Evaluation of a Random-Forest-Weighted Deterministic Coefficient Model," Sustainability, MDPI, vol. 15(17), pages 1-21, August.
    4. Haishan Wang & Jian Xu & Shucheng Tan & Jinxuan Zhou, 2023. "Landslide Susceptibility Evaluation Based on a Coupled Informative–Logistic Regression Model—Shuangbai County as an Example," Sustainability, MDPI, vol. 15(16), pages 1-17, August.
    5. Longye Hu & Chaode Yan, 2024. "Evaluation of Landslide Susceptibility of Mangshan Mountain in Zhengzhou Based on GWO-1D CNN Model," Sustainability, MDPI, vol. 16(12), pages 1-23, June.
    6. Li Zhuo & Yupu Huang & Jing Zheng & Jingjing Cao & Donghu Guo, 2023. "Landslide Susceptibility Mapping in Guangdong Province, China, Using Random Forest Model and Considering Sample Type and Balance," Sustainability, MDPI, vol. 15(11), pages 1-23, June.
    7. Kai Yuan & Biao Hu & Xinlong Li & Tingyun Niu & Liang Zhang, 2023. "Exploration of Coupling Effects in the Digital Economy and Eco-Economic System Resilience in Urban Areas: Case Study of the Beijing-Tianjin-Hebei Urban Agglomeration," Sustainability, MDPI, vol. 15(9), pages 1-28, April.

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