基于PS-InSAR和随机森林的天津区域地表形变监测  

Surface Deformation Monitoring of Tianjin Area Based onPS-InSAR and Random Forest

作　　者：司新毅 谢新民[1] 李盛 SI Xinyi;XIE XinminLI Sheng(China Institute of Water Resources and Hydropower Research,Beijing 100038,China;China Water Investment Co Ltd,Beijing 100053,China;Huai’an Water Supply Co Ltd,Huai’an 223002,China)

机构地区：[1]中国水利水电科学研究院,北京市100038 [2]中国水务投资有限公司,北京市100053 [3]淮安自来水有限公司,江苏省淮安市223002

出　　处：《大地测量与地球动力学》2023年第7期692-695,766,共5页Journal of Geodesy and Geodynamics

摘　　要：采用2019-01~2022-03共90景Sentinel-1A卫星影像,基于PS-InSAR技术对天津市及其周边地区(下文简称“天津区域”)地表形变进行监测分析。结果表明,沉降主要发生在天津市外围,其中邻近天津市的河北省胜芳镇最大地面沉降速率达80 mm/a。为探究天津区域沉降内因,结合随机森林土地分类结果分析地表形变的地理分布特征,为地质灾害综合治理和地下水资源开发利用提供参考依据。We use 90 Sentinel-1A satellite images acquired from January 2019 to March 2022 to monitor the surface deformation of Tianjin city and surrounding area by utilizing the PS-InSAR method.The results show that the land subsidence is mainly distributed in Shengfang town,Hebei province,near Tianjin city,with a maximum deformation rate reaching 80 mm/a.To explore the internal causes of settlement in Tianjin area,we analyze the geographical distribution of surface deformation by combining random forest land classification,which provides reference for the comprehensive management of geological disaster and the development and utilization of groundwater resources.

关 键 词：地面沉降 地下水 PS-INSAR 随机森林 

分 类 号：P237[天文地球—摄影测量与遥感]