Ground Deformation in Yuxi Basin Based on Atmosphere-Corrected Time-Series InSAR Integrated with the Latest Meteorological Reanalysis Data

Time-series interferometric synthetic aperture radar (TS-InSAR) is often affected by tropospheric artifacts caused by temporal and spatial variability in the atmospheric refractive index. Conventional temporal and spatial filtering cannot effectively distinguish topography-related stratified delays,...

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Veröffentlicht in:Remote sensing (Basel, Switzerland) Switzerland), 2022-11, Vol.14 (22), p.5638
Hauptverfasser: Guo, Shipeng, Zuo, Xiaoqing, Wu, Wenhao, Li, Fang, Li, Yongfa, Yang, Xu, Zhu, Shasha, Zhao, Yanxi
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Sprache:eng
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Zusammenfassung:Time-series interferometric synthetic aperture radar (TS-InSAR) is often affected by tropospheric artifacts caused by temporal and spatial variability in the atmospheric refractive index. Conventional temporal and spatial filtering cannot effectively distinguish topography-related stratified delays, leading to biased estimates of the deformation phases. Here, we propose a TS-InSAR atmospheric delay correction method based on ERA-5; the robustness and accuracy of ERA-5 data under the influence of different atmospheric delays were explored. Notably, (1) wet delay was the main factor affecting tropospheric delay within the interferogram; the higher spatial and temporal resolution of ERA-5 can capture the wet delay signal better than MERRA-2. (2) The proposed method can mitigate the atmospheric delay component in the interferogram; the average standard deviation (STD) reduction for the Radarsat-2 and Sentinel-1A interferograms were 19.68 and 14.75%, respectively. (3) Compared to the empirical linear model, the correlation between the stratified delays estimated by the two methods reached 0.73. We applied this method for the first time to a ground subsidence study in the Yuxi Basin and successfully detected three subsidence centers. We analyzed and discussed ground deformation causes based on rainfall and fault zones. Finally, we verified the accuracy of the proposed method by using leveling monitoring data.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14225638