IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i17p12691-d1222454.html
   My bibliography  Save this article

Geological Disaster Susceptibility Evaluation of a Random-Forest-Weighted Deterministic Coefficient Model

Author

Listed:
  • Shaohan Zhang

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
    Yunnan International Joint Laboratory of Critical Mineral Resource, Kunming 650500, China)

  • Shucheng Tan

    (Yunnan International Joint Laboratory of Critical Mineral Resource, Kunming 650500, China
    School of Earth Science, Yunnan University, Kunming 650500, China)

  • Jinxuan Zhou

    (Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650500, China
    Yunnan International Joint Laboratory of Critical Mineral Resource, Kunming 650500, China)

  • Yongqi Sun

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

  • Duanyu Ding

    (Faculty of Architecture and City Planning, Kunming University of Science and Technology, Kunming 650500, China)

  • Jun Li

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

Abstract

An assessment of regional vulnerability to geological disasters can directly indicate the extent and intensity of risks within the study area; thus, providing precise guidance for disaster management efforts. However, in the evaluation of geological disaster susceptibility using a single deterministic coefficient model, the direct superimposition of deterministic coefficient values for each evaluation factor, without considering their objective weights, can impact the accuracy of susceptibility zoning outcomes. To address this limitation, this research proposes a novel approach: geological disaster susceptibility evaluation using a random-forest-weighted deterministic coefficient model. In this method, the objective weight of each evaluation factor is calculated based on a deterministic coefficient model and a parameter-optimized random forest model. By weighting and superimposing the deterministic coefficient values of each evaluation factor, a comprehensive deterministic coefficient map is generated. This map is further divided using the natural breakpoint method to obtain a geological disaster susceptibility zoning map. To validate the accuracy of the evaluation results, partition statistics and the ROC (Receiver Operating Characteristic) curve of the test sample points are utilized. The findings demonstrate that the model performs well in evaluating geological disaster susceptibility in Huize County. The evaluation results are considered reliable and accurate, highlighting the effectiveness of the proposed approach for assessing and zoning geological disaster susceptibility in the region.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:12691-:d:1222454
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/17/12691/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/17/12691/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Xiaoyi Wu & Yuanbao Song & Wei Chen & Guichuan Kang & Rui Qu & Zhifei Wang & Jiaxian Wang & Pengyi Lv & Han Chen, 2023. "Analysis of Geological Hazard Susceptibility of Landslides in Muli County Based on Random Forest Algorithm," Sustainability, MDPI, vol. 15(5), pages 1-17, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xin Zhang & Lijun Jiang & Wei Deng & Zhile Shu & Meiben Gao & Guichuan Liu, 2024. "Risk Assessment of Geological Hazards in the Alpine Gorge Region and Its Influencing Factors: A Case Study of Jiulong County, China," Sustainability, MDPI, vol. 16(5), pages 1-16, February.
    2. Ruixia Ma & Yan Lyu & Tianbao Chen & Qian Zhang, 2023. "Preliminary Risk Assessment of Geological Disasters in Qinglong Gorge Scenic Area of Taihang Mountain with GIS Based on Analytic Hierarchy Process and Logistic Regression Model," Sustainability, MDPI, vol. 15(22), pages 1-19, November.
    3. Jinming Zhang & Jianxi Qian & Yuefeng Lu & Xueyuan Li & Zhenqi Song, 2024. "Study on Landslide Susceptibility Based on Multi-Model Coupling: A Case Study of Sichuan Province, China," Sustainability, MDPI, vol. 16(16), pages 1-22, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. Ming Li & Linlong Li & Yangqi Lai & Li He & Zhengwei He & Zhifei Wang, 2023. "Geological Hazard Susceptibility Analysis Based on RF, SVM, and NB Models, Using the Puge Section of the Zemu River Valley as an Example," Sustainability, MDPI, vol. 15(14), pages 1-21, July.
    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. 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.
    7. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:17:p:12691-:d:1222454. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.