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Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics
Remote Sens. 2013, 5(4), 1774-1786; doi:10.3390/rs5041774
Article

Deformation Trend Extraction Based on Multi-Temporal InSAR in Shanghai

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Received: 10 February 2013 / Revised: 1 April 2013 / Accepted: 2 April 2013 / Published: 11 April 2013
(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)
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Abstract

Shanghai is a modern metropolis characterized by high urban density and anthropogenic ground motions. Although traditional deformation monitoring methods, such as GPS and spirit leveling, are reliable to millimeter accuracy, the sparse point subsidence information makes understanding large areas difficult. Multiple temporal space-borne synthetic aperture radar interferometry is a powerful high-accuracy (sub-millimeter) remote sensing tool for monitoring slow ground deformation for a large area with a high point density. In this paper, the Interferometric Point Target Time Series Analysis method is used to extract ground subsidence rates in Shanghai based on 31 C-Band and 35 X-Band synthetic aperture radar (SAR) images obtained by Envisat and COSMO SkyMed (CSK) satellites from 2007 to 2010. A significant subsidence funnel that was detected is located in the junction place between the Yangpu and the Hongkou Districts. A t-test is formulated to judge the agreements between the subsidence results obtained by SAR and by spirit leveling. In addition, four profile lines crossing the subsidence funnel area are chosen for a comparison of ground subsidence rates, which were obtained by the two different band SAR images, and show a good agreement.
Keywords: MT-InSAR; deformation monitoring; non-uniform subsidence; validation; ASAR; CSK; IPTA MT-InSAR; deformation monitoring; non-uniform subsidence; validation; ASAR; CSK; IPTA
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Chen, J.; Wu, J.; Zhang, L.; Zou, J.; Liu, G.; Zhang, R.; Yu, B. Deformation Trend Extraction Based on Multi-Temporal InSAR in Shanghai. Remote Sens. 2013, 5, 1774-1786.

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