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http://hdl.handle.net/10397/110174
Title: | A multi-satellite SBAS for retrieving long-term ground displacement time series | Authors: | Amr, D Ding, XL Fekry, R |
Issue Date: | May-2024 | Source: | Remote sensing, May 2024, v. 16, no. 9, 1520 | Abstract: | Ground deformation is one of the crucial issues threatening many cities in both societal and economic aspects. Interferometric synthetic aperture radar (InSAR) has been widely used for deformation monitoring. Recently, there has been an increasing availability of massive archives of SAR images from various satellites or sensors. This paper introduces Multi-Satellite SBAS that exploits complementary information from different SAR data to generate integrated long-term ground displacement time series. The proposed method is employed to create the vertical displacement maps of Almokattam City in Egypt from 2000 to 2020. The experimental results are promising using ERS, ENVISAT ASAR, and Sentinel-1A displacement integration. There is a remarkable deformation in the vertical direction along the west area while the mean deformation velocity is −2.32 mm/year. Cross-validation confirms that the root mean square error (RMSE) did not exceed 2.8 mm/year. In addition, the research findings are comparable to those of the previous research in the study area. Consequently, the proposed integration method has great potential to generate displacement time series based on multi-satellite SAR data; however, it still requires further evaluation using field measurements. | Keywords: | Almokattam city DInSAR Ground displacement SBAS |
Publisher: | MDPI AG | Journal: | Remote sensing | EISSN: | 2072-4292 | DOI: | 10.3390/rs16091520 | Rights: | Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). The following publication Amr D, Ding X-L, Fekry R. A Multi-Satellite SBAS for Retrieving Long-Term Ground Displacement Time Series. Remote Sensing. 2024; 16(9):1520 is available at https://doi.org/10.3390/rs16091520. |
Appears in Collections: | Journal/Magazine Article |
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remotesensing-16-01520-v2.pdf | 5.63 MB | Adobe PDF | View/Open |
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