Time-series InSAR ground deformation monitoring: Atmospheric delay modeling and estimating
2019
Li, Zhiwei | Cao, Yunmeng | Wei, Jianchao | Duan, Meng | Wu, Lixin | Hou, Jingxing | Zhu, Jianjun
Spatial heterogeneity in the atmospheric refractive index causes variations in spaceborne interferometric synthetic aperture radar (InSAR) observations. The neutral atmospheric delay (i.e., the tropospheric delay) on one hand, can introduce large errors in the InSAR-derived displacements associated with earthquakes, volcanic activity, glacier motions, underground resource extraction, and many other crustal deformation phenomena. On the other hand, the tropospheric delay can be used to infer high-resolution maps of the non-differential atmospheric water vapor. Time-series InSAR techniques aim to measure geodetic and/or geophysical parameters of interest by integrating time series of SAR images or interferograms using statistical or adjustment methods, through the reduction of error sources (e.g., atmospheric delays, decorrelation noises). This contribution is intended to systematically review the properties, mitigation, and estimation of the atmospheric delays in TS-InSAR for better monitoring ground deformation. We first review the present TS-InSAR techniques and introduce the spatio-temporal characteristics of the neutral atmospheric delays observed in TS-InSAR. We then present the estimates and integration of atmospheric stochastic models for TS-InSAR applications. We construct, analyze, and illustrate a high-resolution non-differential atmospheric water vapor model from TS-InSAR observations. Finally, we present a discussion and outlook for the TS-InSAR atmospheric delay models and estimation efforts.
اظهر المزيد [+] اقل [-]الكلمات المفتاحية الخاصة بالمكنز الزراعي (أجروفوك)
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