{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T17:33:24Z","timestamp":1776101604003,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T00:00:00Z","timestamp":1655942400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA20020101"],"award-info":[{"award-number":["XDA20020101"]}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA20060303"],"award-info":[{"award-number":["XDA20060303"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA20020101"],"award-info":[{"award-number":["XDA20020101"]}]},{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA20060303"],"award-info":[{"award-number":["XDA20060303"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/rs14133009","type":"journal-article","created":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T22:43:00Z","timestamp":1656024180000},"page":"3009","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Using InSAR and PolSAR to Assess Ground Displacement and Building Damage after a Seismic Event: Case Study of the 2021 Baicheng Earthquake"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1623-5707","authenticated-orcid":false,"given":"Xiaolin","family":"Sun","sequence":"first","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Xi","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China"}]},{"given":"Liao","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China"}]},{"given":"Weisheng","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"},{"name":"Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China"}]},{"given":"Xixuan","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9994-9627","authenticated-orcid":false,"given":"Lili","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5996-1525","authenticated-orcid":false,"given":"Yuan","family":"Yao","sequence":"additional","affiliation":[{"name":"Xinjiang Pamir Intracontinental Subduction National Field Observation and Research Station, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/S0924-2716(01)00025-9","article-title":"Photogrammetry and geographic information systems for quick assessment, documentation and analysis of earthquakes","volume":"55","author":"Altan","year":"2001","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"0034","DOI":"10.1016\/j.rse.2018.03.004","article-title":"Earthquake damage mapping: An overall assessment of ground surveys and VHR image change detection after L\u2019Aquila 2009 earthquake","volume":"210","author":"Anniballe","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1016\/j.rse.2005.08.004","article-title":"Remote sensing of landslides: An analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments","volume":"98","author":"Metternicht","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1520","DOI":"10.1109\/TGRS.2007.895830","article-title":"Satellite image analysis for disaster and crisis-management support","volume":"45","author":"Voigt","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.isprsjprs.2013.06.011","article-title":"A comprehensive review of earthquake-induced building damage detection with remote sensing techniques","volume":"84","author":"Dong","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.isprsjprs.2015.09.002","article-title":"Estimating deformation due to soil liquefaction in Urayasu city, Japan using permanent scatterers","volume":"109","author":"ElGharbawi","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Moya, L., Marval Perez, L.R., Mas, E., Adriano, B., Koshimura, S., and Yamazaki, F. (2018). Novel unsupervised classification of collapsed buildings using satellite imagery, ha-zard scenarios and fragility functions. Remote Sens., 10.","DOI":"10.3390\/rs10020296"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Ge, P., Gokon, H., Meguro, K., and Koshimura, S. (2019). Study on the intensity and co-herence information of high-resolution ALOS-2 SAR images for rapid massive land-slide mapping at a pixel level. Remote Sens., 11.","DOI":"10.3390\/rs11232808"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2013.12.009","article-title":"Introducing mapping standards in the quality assessment of buildings extracted from very high resolution satellite imagery","volume":"90","author":"Freire","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.isprsjprs.2015.03.017","article-title":"Landslide deformation monitoring using point-like target offset tracking with multi-mode high-resolution TerraSAR-X data","volume":"105","author":"Shi","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.isprsjprs.2019.04.014","article-title":"Urban flood mapping with an active self-learning convolutional neural network based on TerraSAR-X intensity and interferometric coherence","volume":"152","author":"Li","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.isprsjprs.2014.04.001","article-title":"A review of ground-based SAR interferometry for deformation measurement","volume":"93","author":"Monserrat","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2211","DOI":"10.1016\/j.rse.2010.04.023","article-title":"Surface displacement of the Mw 7 Machaze earthquake (Mozambique): Complementary use of multiband InSAR and radar amplitude image correlation with elastic modelling","volume":"114","author":"Raucoules","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1571","DOI":"10.1109\/TGRS.2006.883149","article-title":"Coherence- and amplitude-based analysis of seismogenic damage in Bam, Iran, using ENVISAT ASAR data","volume":"5","author":"Arciniegas","year":"2007","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1186\/s40623-016-0513-2","article-title":"Detection of damaged urban areas using interferometric SAR coherence change with PALSAR-2","volume":"68","author":"Watanabe","year":"2016","journal-title":"Earth Planets Space"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/36.551935","article-title":"An entropy based classification scheme for land applica-tions of polarimetric SAR","volume":"35","author":"Cloude","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1109\/36.673687","article-title":"A three-component scattering model for polarimetric SAR data","volume":"36","author":"Freeman","year":"1998","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2251","DOI":"10.1109\/TGRS.2010.2099124","article-title":"Four component scattering power decomposition with rotation of coherency matrix","volume":"9","author":"Yamaguchi","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"083595","DOI":"10.1117\/1.JRS.8.083595","article-title":"Unsupervised polarimetric synthetic aperture radar classification of large-scale landslides caused by Wenchuan earthquake in hue-saturation-intensity color space","volume":"8","author":"Li","year":"2014","journal-title":"J. Appl. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Guo, H., Liu, L., Fan, X., Li, X., and Zhang, L. (2012). Earth Observation for Earthquake Disaster Monitoring and Assessment. Earthquake Research and Analysis-Statistical Studies, Observations and Planning, Intech.","DOI":"10.5772\/28055"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2111","DOI":"10.3390\/rs2092111","article-title":"Building damage estimation by integration of seismic intensity information and satellite l-band Sar imagery","volume":"2","author":"Matsuoka","year":"2010","journal-title":"Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"S183","DOI":"10.1193\/1.4000120","article-title":"Extraction of tsunami-flooded areas and damaged buildings in the 2011 Tohoku-Oki earthquake from terrasar-x intensity images","volume":"29","author":"Liu","year":"2013","journal-title":"Earthq. Spectra"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"225","DOI":"10.20965\/jdr.2016.p0225","article-title":"Object-based method for estimating tsunami-induced damage using TerraSAR-X data","volume":"11","author":"Gokon","year":"2016","journal-title":"J. Disaster Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1193\/033014EQS042M","article-title":"Building damage assessment using high-resolution satellite Sar images of the 2010 Haiti earthquake","volume":"32","author":"Miura","year":"2016","journal-title":"Earthq. Spectra"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"241","DOI":"10.20965\/jdr.2017.p0241","article-title":"Extraction of collapsed buildings in the 2016 Kumamoto earthquake using multi-temporal palsar-2 data","volume":"12","author":"Liu","year":"2017","journal-title":"J. Disaster Res."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/LGRS.2017.2772349","article-title":"A framework of rapid regional tsunami damage recognition from post-event TerraSAR-X imagery using deep neural networks","volume":"15","author":"Bai","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1038\/364138a0","article-title":"The displacement field of the Landers earthquake mapped by radar interferometry","volume":"364","author":"Massonnet","year":"1993","journal-title":"Nature"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"8952","DOI":"10.1080\/01431161.2013.860566","article-title":"Damage assessment in urban areas using post-earthquake airborne PolSAR imagery","volume":"34","author":"Zhao","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Karimzadeh, S., Matsuoka, M., Miyajima, M., Adriano, B., Fallahi, A., and Karashi, J. (2018). Sequential SAR Coherence Method for the Monitoring of Buildings in Sarpole-Zahab, Iran. Remote Sens., 10.","DOI":"10.3390\/rs10081255"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"e2021EA001995","DOI":"10.1029\/2021EA001995","article-title":"A Shallow and left-lateral rupture event of the 2021 Mw 5.3 Baicheng earthquake: Implications for the diffuse deformation of Southern Tianshan","volume":"9","author":"Yao","year":"2022","journal-title":"Earth Space Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1758","DOI":"10.1002\/2016GL072253","article-title":"Toward Full Exploitation of Coherent and Incoherent Information in Sentinel-1 TOPS Data for Retrieving Surface Displacement: Application to the 2016 Kumamoto (Japan) Earthquake","volume":"44","author":"Jiang","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_32","first-page":"179","article-title":"A nonlinear inversion of InSAR-observed coseismic surface deformation for estimating variable fault dips in the 2008 Wenchuan earthquake","volume":"76","author":"Chen","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2035","DOI":"10.1785\/0220190302","article-title":"Surface Deformation Related to the 2019 Mw 7.1 and 6.4 Ridgecrest Earthquakes in California from GPS, SAR Interferometry, and SAR Pixel Offsets","volume":"91","author":"Fielding","year":"2020","journal-title":"Seismol. Res. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"He, Z., Chen, T., Wang, M., and Li, Y. (2020). Multi-Segment Rupture Model of the 2016 Kumamoto Earthquake Revealed by InSAR and GPS Data. Remote Sens., 12.","DOI":"10.3390\/rs12223721"},{"key":"ref_35","unstructured":"Matsuoka, M., and Yamazaki, F. (2006, January 25\u201326). Use of SAR imagery for monitoring areas damaged due to the 2006 Mid Java, Indonesia earthquake. Proceedings of the 4th International Workshop on Remote Sensing for Post-Disaster Response 2006, Cambridge, UK."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"18","DOI":"10.25103\/jestr.113.03","article-title":"Urban change detection in TerraSAR image using the difference method and SAR coherence coefficient","volume":"11","author":"Zhang","year":"2018","journal-title":"J. Eng. Sci. Technol. Rev."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"346","DOI":"10.20965\/jdr.2013.p0346","article-title":"Development of earthquake-induced building damage estimation model based on ALOS\/PALSAR observing the 2007 Peru earthquake","volume":"8","author":"Matsuoka","year":"2013","journal-title":"J. Disaster Res."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Karimzadeh, S., and Mastuoka, M. (2017). Building damage assessment using multisensor dual-polarized synthetic aperture radar data for the 2016 M6.2 Amatrice earthquake, Italy. Remote Sens., 9.","DOI":"10.3390\/rs9040330"},{"key":"ref_39","unstructured":"(2021, October 10). Copernicus Open Access Hub. Available online: https:\/\/scihub.copernicus.eu\/."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1585","DOI":"10.1080\/01431160118187","article-title":"Decorrelation of SAR data by urban damages caused by the 1995 Hyogoken-Nanbu earthquake","volume":"22","author":"Yonezawa","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/36.175330","article-title":"Decorrelation in interferometric radar echoes","volume":"30","author":"Zebker","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1109\/LGRS.2004.842375","article-title":"Accurate estimation of correlation in InSAR observations","volume":"2","author":"Zebker","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Sharma, R.C., Tateishi, R., Hara, K., Nguyen, H.T., Gharechelou, S., and Nguyen, L.V. (2017). Earthquake damage visualization (EDV) technique for the rapid detection of earthquake-induced damages using SAR data. Sensors, 17.","DOI":"10.3390\/s17020235"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1109\/JRPROC.1950.230106","article-title":"The transmission and reception of elliptically polarized waves","volume":"38","author":"Sinclair","year":"1950","journal-title":"Proc. IRE"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2343","DOI":"10.1109\/36.964970","article-title":"Quantitative comparison of classification capability: Fully polarimetric versus dual and single-polarization SAR","volume":"39","author":"Lee","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1109\/36.485127","article-title":"A review of target decomposition theorems in radar polarimetry","volume":"34","author":"Cloude","year":"1996","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"23","DOI":"10.20319\/mijst.2019.51.2335","article-title":"Sentinel-1A Analysis for Damage Assessment: A Case Study of Kumamoto Earthquake in 2016","volume":"5","author":"Tamkuan","year":"2019","journal-title":"MATTER Int. J. Sci. Technol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"0924","DOI":"10.1016\/j.isprsjprs.2021.01.022","article-title":"Using a fully polarimetric SAR to detect landslide in complex surroundings: Case study of 2015 Shenzhen landslide","volume":"174","author":"Niu","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_49","first-page":"0034","article-title":"A review on synthetic aperture radar-based building damage assessment in disasters","volume":"240","author":"Pinglan","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1979","DOI":"10.1785\/0220190275","article-title":"Coseismic Displacements and Surface Fractures from Sentinel-1 InSAR: 2019 Ridgecrest Earthquakes","volume":"91","author":"Xu","year":"2020","journal-title":"Seismol. Res. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/S0924-2716(03)00021-2","article-title":"Potential and limits of InSAR data for building reconstruction in built-up areas","volume":"58","author":"Stilla","year":"2003","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"103756","DOI":"10.1016\/j.jobe.2021.103756","article-title":"Satellite radar interferometry: Potential and limitations for structural assessment and monitoring","volume":"46","author":"Talledo","year":"2022","journal-title":"J. Build. Eng."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3009\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:38:27Z","timestamp":1760139507000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/13\/3009"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,23]]},"references-count":52,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14133009"],"URL":"https:\/\/doi.org\/10.3390\/rs14133009","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,23]]}}}