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.
<p>&#160;In InSAR analysis, the effect of microwave propagation delay in the Earth's atmosphere such as the nuetral atmospheric delay and the ionospheric delay is recognized as the primary noise for surface deformation researchs like Earthquake source modeling, tectonic fault motion, and volcanic activity monitoring. Although, for the ionospheric delay, we can now apply the range split spectrum method (SSM) to effectively mitigate it, the mitigation of the neutral atmospheric delay noise remains difficult and is the research problem to be solved. Recently, Arief and Heki (2020) developed a new method to retrieve two-dimensional Zenith Wet Delay (ZWD) distribution at sea level based on the GNSS ZWD and delay gradient derived from the Japanese GNSS network named GEONET. Here we proposed a new InSAR delay correction method based on modifying the Arief and Heki's method and applied it to the ALOS-2 ScanSAR interferograms to evaluate its effectiveness.<br>&#160; In our study, we used 5-minute interval GNSS PPP data provided by the Nevada Geodetic Laboratory in Nevada University, Reno. Since InSAR atmospheric delay contains both hydrostatic and wet components, we estimated two-dimensional Zenith Total Delay (ZTD) distribution at sea level instead of ZWD, and we simaltaneously estimated height dependence of ZTD as a linear function. The model cosists of the regularly distributed grids with 5 km interval and the height dependence. The retrieval of ZTD distribution is performed by the least squares inversion with the smoothing constraint. The retrieved ZTD is then projected onto the InSAR line-of-sight direction and calculated a difference of two epochs to generate an InSAR delay model. Interferograms were generated by RINC ver.0.41r using 16 ALOS-2 ScanSAR level 1.1 full-aperture data covering Kanto Plain in Japan. We applied the SSM to all of interferograms to correct the ionospheric delay noise before applying the proposed tropospheric delay correction.<br>&#160; The result of applying proposed correction method showed that the correction effectively reduced the phase variance, especially in the long-wavelength phase variation. The phase standard deviation (STD) in the whole scene decreased from 35.95 mm to 25.84 mm by applying the proposed GNSS-based correction method. For comparing effectiveness of the proposed method with existing methods, we also calculated the phase STD derived by applying the GACOS model and the numerical weather model-based correction using the Japan Meteorological Agency's Meso-scale model data. The result of comparison showed that the proposed GNSS-based method most reduced the whole-scene phase STD. The GACOS model decreased the STD to 30.96 mm, and the JMA MSM decrease to 27.71 mm, respectively. We then calculate the distance-dependence of the phase STD based on the variogram model. The variogram derived from all the interferograms showed the speriority of the GNSS-based correction, although the STD in distance shorter than 20 km seemed no differences between correction methods.</p>
<p>At the end of 2020, anomalous transient surface deformation was observed by an operational GNSS network at the Noto peninsula, Japan. Although the Noto peninsula locates far from the plate boundary, seismic observations recorded that seismic swarms were accompanied with this transient deformation. Nishimura et al. (2021, presentation at the 2021 Geodetic Society of Japan) estimated that this deformation and swarms may be associated with the intrusion of water from the subducting oceanic plate. Here I performed Sentinel-1 InSAR time series analysis to obtain more detailed view of this transient displacement and to investigate the mechanism of this phenomenon.<br>In the analysis, at first I created interferograms from Sentinel-1 IW SLCs using ISCE2 software. Then these interferograms were used for the LiCSBAS time series analysis. Orbital and topographic fringes were modeled and removed based on precise orbit information and SRTM 1-arcsecond DEM. No atmospheric corrections were applied. I used both ascending and descending paths so that I could calculate 2.5 dimensional analysis to derive quasi-horizontal and quasi-vertical displacements.<br>The result of Sentinel-1 time series showed that the transient displacement seems to start since the end of 2020, which is consistent with the result from the GNSS observation. The estimated largest surface velocities became 13 mm/year in ascending and 15 mm/year in descending. The 2.5 dimensional analysis suggested that the uplift was concentrated at the eastern front of the peninsula, which is also consistent with the GNSS observation. The derived displacement fields suggested that there is an inflation source but this need to be further investigation by, for example, using elastic spherical and/or rectangular fault models.<br>By the presentation, I will perform the InSAR atmospheric correction and source modelling and show these results.</p>
Interferometric Synthetic Aperture Radar (InSAR) often suffers from atmospheric disturbances due to the microwave propagation delay effect, which limits the surface displacement detection accuracy to an order of centimeters or more.Here I developed a new neutral atmospheric delay correction model for InSAR by using the global navigation satellite system (GNSS) zenith total delay (ZTD) and its horizontal gradient data. The proposed model at first retrieves the regularly gridded ZTD distribution at sea level and the linear height dependence from GNSS ZTD and gradient observations by the least squares method. Then, the gridded ZTD is projected onto the InSAR coordinate to correct the neutral atmospheric delay. I evaluated the correction model performance by applying it to L-band ALOS-2/PALSAR-2 ScanSAR interferograms over the Kanto plain in Japan. The correction result showed that by applying the proposed delay correction the phase standard deviation decreased by 33.87 % on average. By comparing it with the generic atmospheric correction online service for InSAR (GACOS) model and the correction by the Japanese regional mesoscale weather model (MSM), the proposed GNSS-based model outperformed others in my test case. The sensitivity test indicated that including the delay gradient could improve delay reproducibility under situations with fewer available GNSS stations. Although the proposed correction model's applicability depends on the number of available GNSS stations at the area of interest, the proposed model has a potential to effectively mitigate the neutral atmospheric delay and to improve the detection ability for smallamplitude surface displacements.
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