A Multi-Satellite SBAS for Retrieving Long-Term Ground Displacement Time Series
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Published:2024-04-25
Issue:9
Volume:16
Page:1520
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ISSN:2072-4292
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Container-title:Remote Sensing
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language:en
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Short-container-title:Remote Sensing
Author:
Amr Doha1ORCID, Ding Xiao-Li1ORCID, Fekry Reda2ORCID
Affiliation:
1. Department of Land Surveying and Geo-Informatics, Hong Kong Polytechnic University, Hong Kong, China 2. Department of Geomatics Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo 11672, Egypt
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.
Reference53 articles.
1. Aboushook, M., EL-Sohby, M., and Mazen, O. (2004, January 19–22). Slope degradation and analysis of Mokattam plateau, Egypt. Proceedings of the 2nd International Conference on Geotechnical Site Characterization (ISC-2), Porto, Portugal. 2. Aimaiti, Y., Yamazaki, F., and Liu, W. (2018). Multi-Sensor InSAR Analysis of Progressive Land Subsidence over the Coastal City of Urayasu, Japan. Remote Sens., 10. 3. Luo, Q., Perissin, D., Lin, H., Li, Q., and Duering, R. (2011, January 24–26). Railway subsidence monitoring by high-resolution INSAR time series analysis in Tianjin. Proceedings of the 2011 19th International Conference on Geoinformatics, Shanghai, China. 4. Sun, Q., Hu, J., Zhang, L., and Ding, X. (2016). Towards Slow-Moving Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets: The Zhouqu Case Study, China. Remote Sens., 8. 5. Sentinel-1 InSAR measurements of deformation over discontinuous permafrost terrain, Northern Quebec, Canada;Wang;Remote Sens. Environ.,2020
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