Open Access
| Issue |
E3S Web Conf.
Volume 637, 2025
2025 International Conference on Environmental Monitoring and Ecological Restoration (EMER 2025)
|
|
|---|---|---|
| Article Number | 01011 | |
| Number of page(s) | 8 | |
| Section | Ecological Restoration Technology and Practice Research | |
| DOI | https://doi.org/10.1051/e3sconf/202563701011 | |
| Published online | 16 July 2025 | |
- Ma Enhua, Li Yimin, Yu Wenxuan, et al. Spatial and temporal distribution characteristics of ground subsidence in Hongta District, Yuxi City based on InSAR [J]. Yangtze River, 2024, 55(S2): 113-120. [Google Scholar]
- Yin Yueping, Zhang Zuochen, Zhang Kaijun. Research on the status quo of land subsidence and its prevention and control countermeasures in China [J]. Chinese Journal of Geological Hazard and Control, 2005(02):1-8. [Google Scholar]
- Ji Zhenfu, Luo Yi, Zhang Guoyuan, et al. Analysis of Ground Subsidence Characteristics and Causes in the Gurao Area of Shantou City [J]. Yunnan Geology, 2024, 43(04): 598-603. [Google Scholar]
- Guo H, Zhang Z, Cheng G, et al. Groundwater- derived land subsidence in the North China Plain[J]. Environmental earth sciences, 2015,74:1415-1427. [Google Scholar]
- Jiang Wen, Li Hui. Over-exploitation of groundwater in Iran leading to depletion of groundwater sources and land subsidence. Journal of Water Resources and Hydropower, 2024, 45(11): 2. [Google Scholar]
- Zhu Jinqi, Gong Xulong, Yu Jun, et al. Research on Ground Subsidence and Ground Crack Prevention and Control in the Suzhou-Wuxi-Changzhou Area [J]. Journal of Geomechanics, 2024, 30(05): 811-833. [Google Scholar]
- Liu He. Research on the Evolution Characteristics of Ground Subsidence in the Beijing Alluvial Plain Driven by New Water Conditions and Layered Overland Flow [J]. Geological Review, 2025, 71(02): 439-451 [Google Scholar]
- Di Shengtong. Study on macro and micro evolution mechanism and trend prediction of the whole process of land subsidence caused by groundwater exploitation[D]. Shandong University, 2020. [Google Scholar]
- Guo Chaojie, Zhang Zhaojiang, Liu Kuo, et al. Surface settlement monitoring and risk analysis in urban Shanghai based on time-series InSAR technology. Surveying and Spatial Geographic Information, 2024, 47(02): 29-31. [Google Scholar]
- Peng Wenxiang, Zhang Deying. Research on Intelligent Prediction Method for Ground Subsidence Based on LSTM and Transformer - A Case Study of Shanghai [J]. Journal of Spatial Information Science, 2024, 31(01): 94-103. [Google Scholar]
- Xiong Fuwen. Research on key technologies for the construction of a benchmark network for accurate monitoring of land subsidence in Shanghai[J]. Shanghai Land & Resources, 2022,43(03):117-123. [Google Scholar]
- Qi Xiequan, Yuan Chao, Cheng Shicai, et al. Prediction of land subsidence in northern Jinan based on MODFLOW groundwater numerical simulation [J]. Chemical and Mineral Geology, 2019, 41(04):277-284. [Google Scholar]
- Qi Xiequan, Zhang Qiang, Yuan Chao, et al. Progress in land subsidence investigation, monitoring and prevention in Jinan City[J]. Shandong Land & Resources, 2019,35(02):53-57. [Google Scholar]
- Wang. Accelerate the construction of the starting area for the conversion of old and new kinetic energy in Jinan[J]. Investment and Cooperation, 2024 (11):74-76. [Google Scholar]
- Edited by Xu Shubai. Analytic Hierarchy Process Principle and Practical Decision-making Method [M]. Tianjin:Tianjin University Press, 1988. [Google Scholar]
- Ouyang Shuangyan. Application of time-series InSAR technology in urban surface deformation monitoring and risk evaluation[D]. Donghua University of Science and Technology, 2022. [Google Scholar]
- Li R. Evaluation of ground subsidence risk in Hebei Plain [D]. Hebei University of Geology, 2020. [Google Scholar]
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