Analysis of Ground Subsidence Evolution Characteristics and Attribution Along the Beijing-Xiong'an Intercity Railway with Time-Series InSAR and Explainable Machine-Learning Technique

被引:0
作者
Liu, Xin [1 ]
Gong, Huili [2 ,3 ]
Zhou, Chaofan [2 ,3 ]
Chen, Beibei [2 ,3 ]
Su, Yanmin [1 ]
Zhu, Jiajun [3 ]
Lu, Wei [2 ]
机构
[1] Heilongjiang Inst Ecol Geol Survey, 904 Bldg,2299 Zhongyuan Ave, Harbin 150028, Peoples R China
[2] Capital Normal Univ, Key Lab Minist Educ Land Subsidence Mech & Prevent, Beijing 100048, Peoples R China
[3] Capital Normal Univ, Coll Resources Environm & Tourism, Beijing 100048, Peoples R China
基金
中国国家自然科学基金;
关键词
PS-InSAR; explainable machine learning; land subsidence; evolution characteristics; attribution analysis;
D O I
10.3390/land14020364
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The long-term overextraction of groundwater in the Beijing-Tianjin-Hebei region has led to the formation of the world's largest groundwater depression cone and the most extensive land subsidence zone, posing a potential threat to the operational safety of high-speed railways in the region. As a critical transportation hub connecting Beijing and the Xiong'an New Area, the Beijing-Xiong'an Intercity Railway traverses geologically complex areas with significant ground subsidence issues. Monitoring and analyzing the causes of land subsidence along the railway are essential for ensuring its safe operation. Using Sentinel-1A radar imagery, this study applies PS-InSAR technology to extract the spatiotemporal evolution characteristics of ground subsidence along the railway from 2016 to 2022. By employing a buffer zone analysis and profile analysis, the subsidence patterns at different stages (pre-construction, construction, and operation) are revealed, identifying the major subsidence cones along the Yongding River, Yongqing, Daying, and Shengfang regions, and their impacts on the railway. Furthermore, the XGBoost model and SHAP method are used to quantify the primary influencing factors of land subsidence. The results show that changes in confined water levels are the most significant factor, contributing 34.5%, with strong interactions observed between the compressible layer thickness and confined water levels. The subsidence gradient analysis indicates that the overall subsidence gradient along the Beijing-Xiong'an Intercity Railway currently meets safety standards. This study provides scientific evidence for risk prevention and the control of land subsidence along the railway and holds significant implications for ensuring the safety of high-speed rail operations.
引用
收藏
页数:22
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