Monitoring of land subsidence by combining small baseline subset interferometric synthetic aperture radar and generic atmospheric correction online service in Qingdao City, China
{"title":"Monitoring of land subsidence by combining small baseline subset interferometric synthetic aperture radar and generic atmospheric correction online service in Qingdao City, China","authors":"Xuepeng Li, Qiuxiang Tao, Yang Chen, Anye Hou, Ruixiang Liu, Yixin Xiao","doi":"10.1117/1.jrs.18.014506","DOIUrl":null,"url":null,"abstract":"Owing to accelerated urbanization, land subsidence has damaged urban infrastructure and impeded sustainable economic and social development in Qingdao City, China. Combining interferometric synthetic aperture radar (InSAR) and generic atmospheric correction online service (GACOS), atmospheric correction has not yet been investigated for land subsidence in Qingdao. A small baseline subset of InSAR (SBAS InSAR), GACOS, and 28 Sentinel-1A images were combined to produce a land subsidence time series from January 2019 to December 2020 for the urban areas of Qingdao, and the spatiotemporal evolution of land subsidence before and after GACOS atmospheric correction was compared, analyzed, and verified using leveling data. Our work demonstrates that the overall surface condition of the Qingdao urban area is stable, and subsidence areas are mainly concentrated in the coastal area of Jiaozhou Bay, northwestern Jimo District, and northern Chengyang District. The GACOS atmospheric correction could reduce the root-mean-square error of the differential interferometric phase. The land subsidence time series after correction was in better agreement with the leveling-monitored results. It is effective to perform GACOS atmospheric correction to improve the accuracy of SBAS InSAR-monitored land subsidence over a large scale and long time series in coastal cities.","PeriodicalId":54879,"journal":{"name":"Journal of Applied Remote Sensing","volume":"210 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Remote Sensing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1117/1.jrs.18.014506","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Owing to accelerated urbanization, land subsidence has damaged urban infrastructure and impeded sustainable economic and social development in Qingdao City, China. Combining interferometric synthetic aperture radar (InSAR) and generic atmospheric correction online service (GACOS), atmospheric correction has not yet been investigated for land subsidence in Qingdao. A small baseline subset of InSAR (SBAS InSAR), GACOS, and 28 Sentinel-1A images were combined to produce a land subsidence time series from January 2019 to December 2020 for the urban areas of Qingdao, and the spatiotemporal evolution of land subsidence before and after GACOS atmospheric correction was compared, analyzed, and verified using leveling data. Our work demonstrates that the overall surface condition of the Qingdao urban area is stable, and subsidence areas are mainly concentrated in the coastal area of Jiaozhou Bay, northwestern Jimo District, and northern Chengyang District. The GACOS atmospheric correction could reduce the root-mean-square error of the differential interferometric phase. The land subsidence time series after correction was in better agreement with the leveling-monitored results. It is effective to perform GACOS atmospheric correction to improve the accuracy of SBAS InSAR-monitored land subsidence over a large scale and long time series in coastal cities.
期刊介绍:
The Journal of Applied Remote Sensing is a peer-reviewed journal that optimizes the communication of concepts, information, and progress among the remote sensing community.