Monitoring and analysis of goaf deformation area based on multi-source data in Yibin
This paper utilized Sentinel-1 and ALOS-2 data for synthetic aperture radar (SAR) data suitability analysis and deformation area extraction and monitoring analysis in Yibin. The R-index method was employed to extract geometric distortion information in the study area for suitability analysis. By using Stacking and satellite-based augmentation system (SBAS) techniques,the paper obtained surface deformation results from 2018 to 2021 in Yibin and successfully identified 72 potential hazards,including 17 ground collapses. The monitoring results demonstrate that the use of multiple SAR data can increase the density of surface deformation monitoring points,improve monitoring accuracy,and effectively avoid monitoring blind spots for interferometric synthetic aperture radar (InSAR). ALOS-2 data has a distinct advantage in identifying hazards in densely vegetated areas,while Sentinel-1 data can be used for sequence analysis of hazard points,revealing the deformation characteristics of these points. The research findings provide new insights for hazard identification and monitoring analysis in the study area and offer strong data support for disaster prevention and mitigation.
万方数据
维普
