| 联合多平台InSAR数据集精确估计地表沉降速率场 |
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| 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. |
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| 作者姓名： | 杨梦诗 廖明生 史绪国 张路 |
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| 作者单位： | 1.武汉大学测绘遥感信息工程国家重点实验室, 湖北 武汉, 430079 |
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| 基金项目： | 国家自然科学基金重点项目61331016湖北省自然科学基金重点项目2014CFA047国家重点基础研究发展计划项目（973）2013CB733205 |
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| 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。
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| 关 键 词： | 多平台 联合估计 时间序列InSAR分析技术 最小二乘 |
| 收稿时间： | 2015-07-06 |
Land Subsidence Monitoring by Joint Estimation of Multi-platform Time Series InSAR Observations |
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| Institution: | 1.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China2.Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China |
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| 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. |
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