IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0289846.html
   My bibliography  Save this article

Prediction model with multi-point relationship fusion via graph convolutional network: A case study on mining-induced surface subsidence

Author

Listed:
  • Baoxing Jiang
  • Kun Zhang
  • Xiaopeng Liu
  • Yuxi Lu

Abstract

Accurate prediction of surface subsidence is of significance for analyzing the pattern of mining-induced surface subsidence, and for mining under buildings, railways, and water bodies. To address the problem that the existing prediction models ignore the correlation between subsidence points, resulting in large prediction errors, a Multi-point Relationship Fusion prediction model based on Graph Convolutional Networks (MRF-GCN) for mining-induced subsidence was proposed. Taking the surface subsidence in 82/83 mining area of Yuandian No. 2 Mine in Anhui Province in eastern China as an example, the surface deformation data obtained from 250 InSAR images captured by Sentinel-1A satellite from 2018 to 2022, combined with GNSS observation data, were used for modeling. The deformation pattern of each single observation point was obtained by feeding their deformation observation data into the LSTM encoder, after that, the relationship graph was created based on the correlation between points in the observation network and MRF-GCN was established. Then the prediction results came out through a nonlinear activation function of neural network. The research shows that the R2R2 value of MRF-GCN model was 0.865 0, much larger than that of Long-Short Term Memory (LSTM) and other conventional models, while mean square error (MSE) of MRF-GCN model was 1.59 899, much smaller than that of LSTM and other conventional models. Therefore, the MRF-GCN model has better prediction accuracy than other models and can be applied to predicting surface subsidence in large areas.

Suggested Citation

  • Baoxing Jiang & Kun Zhang & Xiaopeng Liu & Yuxi Lu, 2023. "Prediction model with multi-point relationship fusion via graph convolutional network: A case study on mining-induced surface subsidence," PLOS ONE, Public Library of Science, vol. 18(8), pages 1-17, August.
  • Handle: RePEc:plo:pone00:0289846
    DOI: 10.1371/journal.pone.0289846
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0289846
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0289846&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0289846?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ye-Shuang Xu & Shui-Long Shen & Zheng-Yin Cai & Guo-Yun Zhou, 2008. "The state of land subsidence and prediction approaches due to groundwater withdrawal 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. 45(1), pages 123-135, April.
    Full references (including those not matched with items on IDEAS)

    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. Chengming Jin & Qing Zhan & Yujin Shi & Chengcheng Wan & Huan Zhang & Luna Zhao & Jianli Liu & Tongfei Tian & Zilong Liu & Jiahong Wen, 2025. "Quantifying Land Subsidence Probability and Intensity Using Weighted Bayesian Modeling in Shanghai, China," Land, MDPI, vol. 14(3), pages 1-20, February.
    2. Yiyue Wang & Runyu Fan & Jining Yan & Min Jin & Xinya Lei & Yuewei Wang & Weijing Song, 2025. "An analysis of urban land subsidence susceptibility based on complex network," 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. 121(1), pages 815-837, January.
    3. Bhattarai, Keshav & Adhikari, Ambika P., 2022. "Minimizing Surface Run-off, Improving Underground Water Recharging, and On-site Rain Harvesting in the Kathmandu Valley," SocArXiv tqfns, Center for Open Science.
    4. Xu-Wei Wang & Ye-Shuang Xu, 2022. "Investigation on the phenomena and influence factors of urban ground collapse 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. 113(1), pages 1-33, August.
    5. Ya-Qiong Wang & Shao-Bing Zhang & Long-Long Chen & Yong-Li Xie & Zhi-Feng Wang, 2019. "Field monitoring on deformation of high rock slope during highway construction: A case study in Wenzhou, China," International Journal of Distributed Sensor Networks, , vol. 15(12), pages 15501477198, December.
    6. repec:plo:pone00:0232828 is not listed on IDEAS
    7. Yong Liu & Hai-Jun Huang, 2013. "Characterization and mechanism of regional land subsidence in the Yellow River Delta, 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. 68(2), pages 687-709, September.
    8. Chun-Yong Luo & Shui-Long Shen & Jie Han & Guan-Lin Ye & Suksun Horpibulsuk, 2015. "Hydrogeochemical environment of aquifer groundwater in Shanghai and potential hazards to underground infrastructures," 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. 78(1), pages 753-774, August.
    9. Beibei Hu & Jun Zhou & Shiyuan Xu & Zhenlou Chen & Jun Wang & Dongqi Wang & Lei Wang & Jifa Guo & Weiqing Meng, 2013. "Assessment of hazards and economic losses induced by land subsidence in Tianjin Binhai new area from 2011 to 2020 based on scenario analysis," 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. 66(2), pages 873-886, March.
    10. Huafeng Xu & Bin Liu & Zhigeng Fang, 2014. "New grey prediction model and its application in forecasting land subsidence in coal mine," 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. 71(2), pages 1181-1194, March.
    11. Dayang Xuan & Jialin Xu, 2014. "Grout injection into bed separation to control surface subsidence during longwall mining under villages: case study of Liudian coal mine, 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. 73(2), pages 883-906, September.
    12. Guodong Li & Hongzhi Wang & Zhaoxuan Liu & Honglin Liu & Haitian Yan & Zenwei Liu, 2022. "Effects of Aeolian Sand and Water−Cement Ratio on Performance of a Novel Mine Backfill Material," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    13. repec:osf:socarx:tqfns_v1 is not listed on IDEAS
    14. Ye-Shuang Xu & Yao Yuan & Shui-Long Shen & Zhen-Yu Yin & Huai-Na Wu & Lei Ma, 2015. "Investigation into subsidence hazards due to groundwater pumping from Aquifer II in Changzhou, 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. 78(1), pages 281-296, August.
    15. Yong-Xia Wu & Tian-Liang Yang & Pei-Chao Li & Jin-Xin Lin, 2019. "Investigation of Groundwater Withdrawal and Recharge Affecting Underground Structures in the Shanghai Urban Area," Sustainability, MDPI, vol. 11(24), pages 1-18, December.
    16. Ahmed M. Youssef & Mazen M. Abu Abdullah & Biswajeet Pradhan & Ahmed F. D. Gaber, 2019. "Agriculture Sprawl Assessment Using Multi-Temporal Remote Sensing Images and Its Environmental Impact; Al-Jouf, KSA," Sustainability, MDPI, vol. 11(15), pages 1-16, August.
    17. Ye-Shuang Xu & Shui-Long Shen & Dong-Jie Ren & Huai-Na Wu, 2016. "Analysis of Factors in Land Subsidence in Shanghai: A View Based on a Strategic Environmental Assessment," Sustainability, MDPI, vol. 8(6), pages 1-12, June.
    18. Yu Huang & Hualin Cheng, 2013. "The impact of climate change on coastal geological disasters in southeastern 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. 65(1), pages 377-390, January.
    19. Ye-Shuang Xu & De-Xuan Zhang & Shui-Long Shen & Long-Zhu Chen, 2009. "Geo-hazards with characteristics and prevention measures along the coastal regions of 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. 49(3), pages 479-500, June.
    20. Ye-Shuang Xu & Run-Qiu Huang & Jie Han & Shui-Long Shen, 2013. "Evaluation of allowable withdrawn volume of groundwater based on observed data," 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. 67(2), pages 513-522, June.
    21. Guangyun Gao & Shaofeng Yao & Yujun Cui & Qingsheng Chen & Xianlin Zhang & Kewen Wang, 2018. "Zoning of confined aquifers inrush and quicksand in Shanghai region," 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. 91(3), pages 1341-1363, April.
    22. Keren Dai & Xianlin Shi & Jisong Gou & Leyin Hu & Mi Chen & Liang Zhao & Xiujun Dong & Zhenhong Li, 2020. "Diagnosing Subsidence Geohazard at Beijing Capital International Airport, from High-Resolution SAR Interferometry," Sustainability, MDPI, vol. 12(6), pages 1-16, March.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0289846. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.