杨梦诗, 廖明生, 史绪国, 张路. 联合多平台InSAR数据集精确估计地表沉降速率场[J]. 武汉大学学报 ( 信息科学版), 2017, 42(6): 797-802. DOI: 10.13203/j.whugis20140924
引用本文: 杨梦诗, 廖明生, 史绪国, 张路. 联合多平台InSAR数据集精确估计地表沉降速率场[J]. 武汉大学学报 ( 信息科学版), 2017, 42(6): 797-802. DOI: 10.13203/j.whugis20140924
YANG Mengshi, LIAO Mingsheng, SHI Xuguo, ZHANG Lu. Land Subsidence Monitoring by Joint Estimation of Multi-platform Time Series InSAR Observations[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6): 797-802. DOI: 10.13203/j.whugis20140924
Citation: YANG Mengshi, LIAO Mingsheng, SHI Xuguo, ZHANG Lu. Land Subsidence Monitoring by Joint Estimation of Multi-platform Time Series InSAR Observations[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6): 797-802. DOI: 10.13203/j.whugis20140924

联合多平台InSAR数据集精确估计地表沉降速率场

Land Subsidence Monitoring by Joint Estimation of Multi-platform Time Series InSAR Observations

  • 摘要: 分析了不同平台InSAR数据集的成像几何差异以及时空分辨率不一致对沉降场联合反演的影响,提出了多平台InSAR数据联合估计方法及其解决方案。将该方法应用于分析覆盖上海地区的18景TerraSAR-X、16景ENVISAT ASAR和20景ALOS PALSAR数据,提取了数据共同覆盖时间段内(2009年~2010年)的上海市地表沉降速率场分布,并与同期获取的水准数据进行了对比验证。实验结果表明,本文方法能有效的联合多组观测数据给出更精确的沉降估计结果,且无需外部数据校正。

     

    Abstract: A method for estimating the land subsidence velocity field was proposed by combining m ulti-platform InSARdata set. The precise estimation of subsidence could be achieved by combing redun-dant observations.However, the key problems to be solved in integration of different SAR datasetsincluded different imaging geo metries and inconsistent spatial/tem poral resolutions.We discussed allthese problems in detail and given one solution. Our method then was applied to detect unbiased long-term velocity field in Shanghai, China with 18 Terra SAR-X、16 ENVISAT ASARand 20 ALOS PAL-SAR datasets. Firstly, large-scale velocity maps from three SAR data stacks were extracted whichshow similar deformation patterns and different nu merical ranges. Then, weighted least squares ad-justment was used to derive unbiased velocity field. The experimental results were validated with lev-eling data. The experiment results show that combing multi-platform InSA R data achieved precise es-timation of deformation without any prioriinformation.

     

/

返回文章
返回