光学卫星辅助的SBAS-InSAR技术在大范围地表形变监测中的应用  

Application of optical satellite-assisted SBAS-InSAR technology in large-scale surface deformation monitoring

作　　者：胡智峰 李禄 HU Zhifeng;LI Lu(China Coal Aerial Remote Sensing Group Co.,Ltd.,Xi’an 710199,China;School of Automation,Beijing Information Science&Technology University,Beijing 100192,China)

机构地区：[1]中煤航测遥感集团有限公司,西安710199 [2]北京信息科技大学自动化学院,北京100192

出　　处：《北京信息科技大学学报（自然科学版）》2024年第5期67-73,共7页Journal of Beijing Information Science and Technology University（Science and Technology Edition）

基　　金：国家自然科学基金项目(61901471,62471049)。

摘　　要：工程施工对自然地貌的破坏易引发地质灾害,采用多时相合成孔径雷达干涉测量(interferometric synthetic aperture radar,InSAR)技术对地表进行形变监测可以有效预测这些灾害。然而传统的InSAR方法只能提取三维形变信息,无法分析土壤水文、植被覆盖等与形变诱因相关的地质情况。因此,使用光学遥感卫星GF-2的多光谱数据辅助多时相的哨兵-1A雷达卫星升轨影像作为数据源,采用基于角反射器的小基线集InSAR(small baselines subset InSAR,SBAS-InSAR)技术,对长庆油田第三输油管线附近进行了地表形变分析和灾害识别。应用该方法预测出41处地质灾害隐患点,灾害覆盖率为100%,识别整体精度达到92.86%,监测精度优于1 cm,验证了方法的有效性。The destruction of natural landform by engineering construction is prone to geological disasters,which can be effectively predicted by surface deformation monitoring using the multi-temporal interferometric synthetic aperture radar(InSAR)technology.However,traditional InSAR only extract three-dimensional deformation information and cannot analyze geological conditions related to deformation triggers such as soil hydrology,vegetation cover.Therefore,surface deformation analysis and disaster identification were conducted near the third oil pipeline in Changqing Oilfield,by taking multispectral data from optical remote sensing satellite GF-2 to assist multi-temporal Sentinel-1A radar satellite ascending orbit imagery as the data source,and using small baselines subset InSAR(SBAS-InSAR)technology based on corner reflectors.The proposed method predicates 41 potential geological hazard hidden points,with a disaster coverage rate of 100%,an overall accuracy of 92.86%and monitoring accuracy better than 1 cm,verifying the effectiveness of the proposed method.

关 键 词：多源遥感 灾害监测 地表形变 SBAS-InSAR 哨兵-1A GF-2 

分 类 号：TP237[自动化与计算机技术—检测技术与自动化装置]