From Deformation Monitoring to Mechanism Insight: Assessing Sudden Subsidence Risk via an Improved 2D SBAS-InSAR and Physical Modeling Approach

Safe and efficient coal mining faces a global challenge in predicting sudden surface subsidence whose mechanisms remain unclear. This study, centered on deep coal seams in China's Ordos Basin, examines the risk of abrupt subsidence controlled by high-positioned, ultra-thick, and weakly cemented key strata. We adopt an integrated "observation-experiment-model" paradigm. First, we construct a spatial decoupling model to analyze errors in 1D SBAS-InSAR monitoring, leading to a refined 2D method that reduces the three-dimensional monitoring error from 50 mm to under 20 mm. Based on this, the subsidence basin's boundary angles are accurately determined as 52.3°-58.6° (strike) and 44.3°-48.2° (dip). Second, a large-scale physical simulation experiment visualizes the complete process of overburden failure up to the breaking of high-level key strata. Finally, by coupling remote sensing observations with experimental phenomena, a theoretical model is built to quantify the mechanical behavior of key strata, revealing the critical width-to-depth ratios for the rupture of the Yan'an Formation (0.21-0.27), Zhiluo Formation (0.53-0.82), and Zhidan Group (1.22-1.34). The research not only delineates surface subsidence morphology under special geological conditions but also answers the core questions of why subsidence occurs and when mutation may happen, thereby laying a theoretical foundation for a comprehensive early-warning model for mining areas worldwide.

Authors

Institutions

Publication Details

Journal
Sensors
Published
2026-01-14
DOI
https://doi.org/10.3390/s26020562
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

From Deformation Monitoring to Mechanism Insight: Assessing Sudden Subsidence Risk via an Improved 2D SBAS-InSAR and Physical Modeling Approach

Qiu Du, Huaizhan Li, L. Zhang, Guangli Guo et al.
Sensors
Synthetic Aperture Radar (SAR) Applications and Techniques
article

From Deformation Monitoring to Mechanism Insight: Assessing Sudden Subsidence Risk via an Improved 2D SBAS-InSAR and Physical Modeling Approach

Qiu Du, Huaizhan Li, L. Zhang, Guangli Guo, Jingchao Sun, Zhao Hu, Fanzhen Meng
article en

Abstract

Safe and efficient coal mining faces a global challenge in predicting sudden surface subsidence whose mechanisms remain unclear. This study, centered on deep coal seams in China's Ordos Basin, examines the risk of abrupt subsidence controlled by high-positioned, ultra-thick, and weakly cemented key strata. We adopt an integrated "observation-experiment-model" paradigm. First, we construct a spatial decoupling model to analyze errors in 1D SBAS-InSAR monitoring, leading to a refined 2D method that reduces the three-dimensional monitoring error from 50 mm to under 20 mm. Based on this, the subsidence basin's boundary angles are accurately determined as 52.3°-58.6° (strike) and 44.3°-48.2° (dip). Second, a large-scale physical simulation experiment visualizes the complete process of overburden failure up to the breaking of high-level key strata. Finally, by coupling remote sensing observations with experimental phenomena, a theoretical model is built to quantify the mechanical behavior of key strata, revealing the critical width-to-depth ratios for the rupture of the Yan'an Formation (0.21-0.27), Zhiluo Formation (0.53-0.82), and Zhidan Group (1.22-1.34). The research not only delineates surface subsidence morphology under special geological conditions but also answers the core questions of why subsidence occurs and when mutation may happen, thereby laying a theoretical foundation for a comprehensive early-warning model for mining areas worldwide.

SensorsVol. 26(2)
China University of Mining and Technology (CN), China Geological Survey (CN)
Openalex Percentile: Top 91%
Synthetic Aperture Radar (SAR) Applications and Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

From Deformation Monitoring to Mechanism Insight: Assessing Sudden Subsidence Risk via an Improved 2D SBAS-InSAR and Physical Modeling Approach — Qiu Du, Huaizhan Li, et al. · Sensors (2026) | TGRS Research Map | TGRS