Using InSAR and PolSAR to Assess Ground Displacement and Building Damage after a Seismic Event: Case Study of the 2021 Baicheng Earthquake

Abstract

During unexpected earthquake catastrophes, timely identification of damaged areas is critical for disaster management. On the 24 March 2021, Baicheng county was afflicted by a Mw 5.3 earthquake. The disaster resulted in three deaths and many human injuries. As an active remote sensing technology independent of light and weather, the increasingly accessible Synthetic Aperture Radar (SAR) is an attractive data for assessing building damage. This paper aims to use Sentinel-1A radar images to rapidly assess seismic damage in the early phases after the disaster. A simple and robust method is used to complete the task of surface displacement analysis and building disaster monitoring. In order to obtain the coseismic deformation field, differential interferometry, filtering and phase unwrapping are performed on images before and after the earthquake. In order to detect the damage area of buildings, the Interferometric Synthetic Aperture Radar (InSAR) and Polarimetric Synthetic Aperture Radar (PolSAR) techniques are used. A simple and fast method combining coherent change detection and polarimetric decomposition is proposed, and the complete workflow is introduced in detail. In our experiment, we compare the detection results with the ground survey data using an unmanned aerial vehicle (UAV) after the earthquake to verify the performance of the proposed method. The results indicate that the experiment can accurately obtain the coseismic deformation field and identify the damaged and undamaged areas of the buildings. The correct identification accuracy of collapsed and severely damaged areas is 86%, and that of slightly damaged and undamaged areas is 84%. Therefore, the proposed method is extremely effective in monitoring seismic-affected areas and immediately assessing post-earthquake building damage. It provides a considerable prospect for the application of SAR technology.

Advances in Rapid Damage Identification Methods for Post-Disaster Regional Buildings Based on Remote Sensing Images: A Survey

“…Sun et al [108] aimed for rapid earthquake damage assessment in the early postdisaster phase using Sentinel-1A radar images. Their model, applied to the 2021 Mado County earthquake in China, demonstrated success in accurately obtaining the co-seismic deformation field and identifying damaged and undamaged building areas.…”

Unsupervised Structural Damage Assessment from Space using the Segment Anything Model (USDA-SAM): A Case Study of the 2023 Türkiye Earthquake

“…SAR's capabilities have been extensively documented, including three-dimensional reconstructions, cloud penetration, and independence from lighting conditions. InSAR, with its ability to compare SAR images over time, has proven invaluable for detecting subtle ground alterations in seismic zones [6], [7].…”

Seismic multi-hazard and impact estimation via causal inference from satellite imagery

“…Most notably, damage proxy maps (DPMs), developed by researchers of the NASA Advanced Rapid Imaging and Analysis (ARIA) team, extract correlation changes between pre- and post-event images, showing the potential to provide supplementary information for rapid seismic hazard and impact estimation 14 . Recent studies have explored integrating DPMs or other InSAR images with prior geospatial models to estimate or analyze single-type hazard 15 – 17 or building damage 18 , 19 . However, these models (1) all focus on single-type hazards, and (2) they are often trained in a supervised way and need a reasonable amount of ground truth labels for model training—which is not immediately available after earthquakes.…”