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Influence of human activity on landslide susceptibility development in the Three Gorges area

Author

Listed:
  • Yongwei Li

    (China University of Geosciences
    Central South University)

  • Xianmin Wang

    (China University of Geosciences)

  • Hang Mao

    (China University of Geosciences)

Abstract

Human activities are important factors that trigger frequent occurrences of landslides; thus, for landslide control, it is critical to determine the influence of human activity on landslide occurrence probability. The Three Gorges area is a region in the world that typically experiences serious landslide disasters and frequent human activities. The objective of this work is to employ the Three Gorges area as an example to reveal the impact of human activity on the dynamic development of landslide susceptibility from 2010 to 2019. Some new viewpoints are suggested for the five aspects: (1) High-precision landslide susceptibility maps are generated by a combination of multiresolution segmentation and convolutional neural network algorithms. Moreover, the dynamic development rules of landslide susceptibility from 2010 to 2019 are revealed. (2) The change in landslide susceptibility in the study area from 2010 to 2019 was mainly caused by the combined action of rainfall and human activity. The fluctuation of reservoir water level had a less influence on the development of landslide susceptibility. (3) Some human activities, especially road construction, farmland appropriation for building construction, agricultural reclamation, farmland cultivation and irrigation, initiation of commercial planting, urban expansion, and large-scale deforestation, may dramatically increase landslide occurrence probability. (4) Human activities, e.g., conversion of farmland to forestry, artificial recovery of natural vegetation, and later periods of artificial planting, may obviously reduce landslide susceptibility. (5) The human activity causes and mechanisms influencing landslide susceptibility in the study area are proposed, including transpiration and anchorage of plants, slope reinforcement by plant roots, destruction of slope stress equilibrium, and soil erosion.

Suggested Citation

  • Yongwei Li & Xianmin Wang & Hang Mao, 2020. "Influence of human activity on landslide susceptibility development in the Three Gorges area," 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. 104(3), pages 2115-2151, December.
    • Handle: RePEc:spr:nathaz:v:104:y:2020:i:3:d:10.1007_s11069-020-04264-6
    DOI: 10.1007/s11069-020-04264-6
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    References listed on IDEAS

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    1. Soyoung Park & Se-Yeong Hamm & Jinsoo Kim, 2019. "Performance Evaluation of the GIS-Based Data-Mining Techniques Decision Tree, Random Forest, and Rotation Forest for Landslide Susceptibility Modeling," Sustainability, MDPI, vol. 11(20), pages 1-20, October.
    2. Jerome Graff & H. Romesburg & Rafi Ahmad & James McCalpin, 2012. "Producing landslide-susceptibility maps for regional planning in data-scarce regions," 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. 64(1), pages 729-749, October.
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    2. Jie Liu & Zhen Wu & Huiwen Zhang, 2021. "Analysis of Changes in Landslide Susceptibility according to Land Use over 38 Years in Lixian County, China," Sustainability, MDPI, vol. 13(19), pages 1-23, September.
    3. Haoran Fang & Yun Shao & Chou Xie & Bangsen Tian & Chaoyong Shen & Yu Zhu & Yihong Guo & Ying Yang & Guanwen Chen & Ming Zhang, 2023. "A New Approach to Spatial Landslide Susceptibility Prediction in Karst Mining Areas Based on Explainable Artificial Intelligence," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
    4. Siti Norsakinah Selamat & Nuriah Abd Majid & Aizat Mohd Taib, 2023. "A Comparative Assessment of Sampling Ratios Using Artificial Neural Network (ANN) for Landslide Predictive Model in Langat River Basin, Selangor, Malaysia," Sustainability, MDPI, vol. 15(1), pages 1-21, January.
    5. 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.
    6. Xin Wei & Lulu Zhang & Junyao Luo & Dongsheng Liu, 2021. "A hybrid framework integrating physical model and convolutional neural network for regional landslide susceptibility mapping," 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. 109(1), pages 471-497, October.
    7. Hakan Tanyaş & Tolga Görüm & Dalia Kirschbaum & Luigi Lombardo, 2022. "Could road constructions be more hazardous than an earthquake in terms of mass movement?," 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. 112(1), pages 639-663, May.
    8. 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.
    9. Jihyun Yang & Jeffrey Shragge & Aaron J. Girard & Edgard Gonzales & Javier Ticona & Armando Minaya & Richard Krahenbuhl, 2023. "Seismic Characterization of a Landslide Complex: A Case History from Majes, Peru," Sustainability, MDPI, vol. 15(18), pages 1-15, September.
    10. Fanyu Zhang & Jianbing Peng & Xiaowei Huang & Hengxing Lan, 2021. "Hazard assessment and mitigation of non-seismically fatal landslides in China," 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. 106(1), pages 785-804, March.

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