Journal
REMOTE SENSING
Volume 14, Issue 13, Pages -Publisher
MDPI
DOI: 10.3390/rs14133009
Keywords
Baicheng earthquake; building damage assessment; coseismic deformation field; SAR interferometry; SAR polarimetry
Categories
Funding
- Strategic Priority Research Program of Chinese Academy of Sciences [XDA20020101]
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDA20060303]
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This paper uses Synthetic Aperture Radar (SAR) technology to rapidly assess post-earthquake building damage and proposes a simple and fast method. The experiment proves that the method can accurately identify damaged and undamaged areas, providing important reference for post-earthquake building damage assessment.
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.
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