High‐Resolution Water Vapor Maps Obtained by Merging Interferometric Synthetic Aperture Radar and GPS Measurements

Cao, Yunmeng; Duan, Meng; Wei, Jianchao

doi:10.1029/2020jd033430

Cited by 7 publications

(4 citation statements)

References 43 publications

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“…In addition to the Sentinel-1 data, time-series from more than 150 continuous GNSS (Global Navigation Satellite System) sites (Fig. 1), were used to estimate reference shifts between deformation rate maps from different tracks and to correct for possible orbital errors in the InSAR time-series analysis (Cao et al 2021b…”

Section: Interferograms and Time-series Insar Processingmentioning

confidence: 99%

“…As each SAR image is generated from three standard Sentinel‐1 image concatenated along‐track, the total number Sentinel‐1 data products we downloaded is over 3,000. In addition to the Sentinel‐1 data, time series from more than 150 continuous GNSS (Global Navigation Satellite System) sites (Figure 1), were used to estimate reference shifts between deformation rate maps from different tracks and to correct for possible orbital errors in the InSAR time‐series analysis (Cao, Li, et al., 2021).…”

Section: Data Processingmentioning

confidence: 99%

“…We estimated the East, North, and Up velocities of each GNSS station using least‐squares estimation of observations between June 2015 and October 2021, and then we calculated the GNSS velocity along the InSAR LOS direction site by site (Wright, 2004). We model the differences between InSAR‐derived and GNSS‐derived LOS velocities to adjust the InSAR results for reference shift and possible large‐scale long‐wavelength signals (due to possible orbital errors and residual tropospheric delays) by using a first‐order polynomial function (Cao, Li, et al., 2021).…”

Section: Data Processingmentioning

confidence: 99%

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Iceland Kinematics From InSAR

2023

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Time-series of countrywide displacements over Iceland from 2015 to 2021 derived by integrating Sentinel-1 InSAR and GNSS observations • A two-step InSAR tropospheric correction method used to mitigate both short-and long-wavelength tropospheric effects • Results dominated by plate spreading and glacial isostatic adjustment with numerous other smaller-scale signals Abstract Large-scale ground deformation in Iceland is dominated by extensional plateboundary deformation, where the Mid-Atlantic Ridge crosses the island, and by uplift due to glacial isostatic adjustment from thinning and retreat of glaciers. While this deformation is mostly steady over multiple years, it is modulated by smaller-scale transient deformation associated with e.g., earthquakes, volcanic unrest, and geothermal exploitation. Here we combine countrywide Sentinel-1 interferometric synthetic aperture radar (InSAR) data (from six tracks) from 2015 to 2021 with continuous GNSS observations to produce time-series of displacements across Iceland. The InSAR results were improved in a two-step tropospheric mitigation procedure, using (1) global atmospheric models to reduce long-wavelength and topography-correlated tropospheric signals, and (2) modeling of the stochastic properties of the residual troposphere. Our results significantly improve upon earlier country-wide InSAR results, which were based on InSAR stacking, as we use more data, better data weighting, and advanced InSAR corrections to produce time-series of ground displacements instead of just velocities. We fuse the three ascending and three descending track results to estimate maps of East and Up velocities, which clearly show the large-scale extension and GIA deformation. Using a revised plate-spreading and glacial isostatic adjustment models, based on these new ground velocity maps, we remove the large-scale and steady deformation from the InSAR timeseries and analyze the remaining transient deformations. Our results demonstrate the importance of (1) mitigating InSAR tropospheric signals over Iceland and of (2) solving for time-series of deformation, not just velocities, as multiple transient deformation processes are present.

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Section: Interferograms and Time-series Insar Processingmentioning

confidence: 99%

Section: Data Processingmentioning

confidence: 99%

Section: Data Processingmentioning

confidence: 99%

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Iceland Kinematics From InSAR

2023

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“…Interferometric synthetic aperture radar (InSAR) has been used to measure precipitable water vapor (PWV) maps with high spatial resolution (a few tens of meters) (e.g., [8][9][10][11][12]). When microwaves emitted from a satellite travel through the neutral atmosphere, the phase velocity of the microwave is changed, and the travel path is bended due to having a different refractive index to the vacuum.…”

Section: Introductionmentioning

confidence: 99%

Error Evaluation of L-Band InSAR Precipitable Water Vapor Measurements by Comparison with GNSS Observations in Japan

Matsuzawa

Kinoshita

2021

Remote Sensing

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Interferometric synthetic aperture radar (InSAR) enables us to obtain precipitable water vapor (PWV) maps with high spatial resolution through the phase difference caused by refraction in the atmosphere. Although previous studies have evaluated the error level of InSARPWV observations, they validated it only with C-band InSARPWV observations. Since ionospheric disturbance seriously contaminates the InSAR phase in the case of the lower-frequency SAR system, it is necessary for a PWV error level evaluation correcting the ionospheric effect appropriately if we use lower-frequency SAR systems, such as the Advanced Land Observing Satellite-2 (ALOS-2). In this paper, we evaluated the error level of the L-band InSARPWV observation obtained from ALOS-2 data covering four areas in Japan. We compared the InSAR observations with global navigation satellite system (GNSS) atmospheric observations and estimated the L-band InSARPWV error value by utilizing the error propagation theory. As a result, the L-band InSARPWV absolute error reached 2.83 mm, which was comparable to traditional PWV observations. Moreover, we investigated the impacts of the seasonality, the interferometric coherence, and the height dependence on the PWV observation accuracy in InSAR.

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