SMF-POLOPT: an adaptive multitemporal pol(DIn)SAR filtering and phase optimization algorithm for PSI applications

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Speckle noise and decorrelation can hamper the application and interpretation of PolSAR images. In this paper, a new adaptive multitemporal Pol(DIn)SAR filtering and phase optimization algorithm is proposed to address these limitations. This algorithm first categorizes and adaptively filters permanent scatterer (PS) and distributed scatterer (DS) pixels according to their polarimetric scattering mechanisms [i.e., the scattering-mechanism-based filtering (SMF)]. Then, two different polarimetric DInSAR (POLDInSAR) phase OPTimization methods are applied separately on the filtered PS and DS pixels (i.e., POLOPT). Finally, an inclusive pixel selection approach is used to identify high-quality pixels for ground deformation estimation. Thirty-one full-polarization Radarsat-2 SAR images over Barcelona (Spain) and 31 dual-polarization TerraSAR-X images over Murcia (Spain) have been used to evaluate the performance of the proposed algorithm. The PolSAR filtering results show that the speckle of PolSAR images has been well reduced with the preservation of details by the proposed SMF. The obtained ground deformation monitoring results have shown significant improvements, about ×7.2 (the full-polarization case) and ×3.8 (the dual-polarization case) with respect to the classical full-resolution single-pol amplitude dispersion method, on the valid pixels' densities. The excellent PolSAR filtering and ground deformation monitoring results achieved by the adaptive Pol(DIn)SAR filtering and phase optimization algorithm (i.e., the SMF-POLOPT) have validated the effectiveness of this proposed scheme.Peer ReviewedPostprint (author's final draft

ACE-OT: Polarimetric SAR data based amplitude contrast enhancement algorithm for offset tracking applications

The use of polarimetric synthetic aperture radar (SAR) data can improve the performance of persistent scatterer interferometry (PSI). However, its huge potential remains locked for the amplitude information-based offset tracking (OT) technology. For example, to the best knowledge of the authors, there is no single example of a polarization-based image optimization method that has been developed for OT processing. In this article, an amplitude contrast enhancement (ACE) algorithm is introduced, which demonstrates the potential of the polarimetric SAR data on the improvement of OT performance. Its core idea is finding the optimal combination of the different scattering mechanisms for each pixel to improve the contrast. First, the orientation of the reflected polarization ellipse is removed, to avoid the influence of the geometric relationship between the antenna and the target, and the properties of the target. Then three similarity parameters are defined to represent the three basic reflection types of the single bounce, the double bounce, and the random reflection. After that, the optimizing equation is constructed with two optimizing vectors. Finally, the optimizing vectors are calculated to obtain the enhanced amplitude image. Three examples of the enhancement are presented with different PolSAR images sets of both full- (Radarsat-2) and dual-polarization (TerraSAR-X and Sentinel-1). The performance of ACE-OT has been compared with another method, the adaptive histogram enhancement (AHE). The impact of the number of polarization channels available on ACE-OT performance has also been studied.This work was supported in part by the China Scholarship Council under Grant 201806420035, in part by the Spanish Ministry of Science and Innovation (MCIN), in part by the State Research Agency (AEI) Project under Grant PID2020-117303GB-C21 and Grant MCIN/AEI/10.13039/501100011033, in part by the National Natural Science Foundation of China under Grant 42004011, in part by the China Postdoctoral Science Foundation under Grant 2020M671646, and in part by the Construction Program of Space-Air-Ground-Well Cooperative Awareness Spatial Information Project under Grant B20046.Peer ReviewedPostprint (author's final draft

Surface and crustal deformation mechanism of the Dobi graben and surrounding area in the Afar Depression, Ethiopia

Our Study used the Advanced Synthetic Aperture Radar (ASAR), C- Band (h = 5.6 cm) of the ENVISAT satellite ASAR data, Landsat Operational Land Imager (OLI), and Shuttle Radar Topography Mission (SRTM) digital elevation models, as well as the integration of geophysical ground base magnetic survey data, aeromagnetic, and Satellite gravity data, to investigate the time series surface deformation and crustal structure of the Dobi graben and surrounding area. Results from our fault population analysis using SRTM DEM aided by satellite imageries suggest that the direction of the faults' lateral propagations are highly influenced by the two regional volcanic rifts, the Red Sea Rift (RSR) and Gulf of Aden Rift (GAR). Additionally, the Dmax/Lmax ratio of the faults is calculated as ~0.03, which indicates the normal faults in the region can be characterized by the constant displacement fault growth model. Our fault population analysis also indicates that the possible presence of melt material in the lower crust likely acts as a barrier for lateral propagations of the faults. Results from our InSAR analysis suggest that an extension process with a creeping mechanism associated mainly with normal faulting presumably causes subsidence within the graben and uplifting in the rift shoulder. The abnormal, continuous uplifting in the horst area might be associated with the temporary reactivation of normal faulting in the region. Finally, our 2D magnetic and gravity forward modeling revealed the crust to be thinner beneath the Dobi graben, reaching a thickness of only ~23 km. We also found the boundary between the upper and lower crusts to be at depth of between 10 and 12 km. Additionally, we found two ~5 km wide zones where melt and mafic dike intrusions are possibly present within the lower crust. These zones are centered beneath a relay zone on the southwestern side of the Dobi graben and beneath a narrow (~2 km wide) graben just to the northeast of the Dobi graben. We propose that, while the upper crust beneath the Dobi graben is stretching mechanically, the lower crust is stretching ductily, aided by the presence of melt and the intrusion of mafic dikes

Polarimetry-Based Distributed Scatterer Processing Method for PSI Applications

Permanent scatterer interferometry is a multitemporal interferometric synthetic aperture radar technique that produces high-accuracy ground deformation measurement. A high density of permanent scatterer (PS) is required to provide accurate results. In natural environments with low PS density, distributed scatterers (DSs) could serve as additional coherent observations. This paper introduces a polarimetric scattering property-based adaptive filtering method that preserves PS candidates and filters DS candidates. To further increase the coherence estimate of DS candidates, the technique includes a complex coherence decomposition that adaptively selects the most stable scattering mechanisms, thus improving pixel coherence estimation. The proposed method was evaluated on 11 quad-polarized ALOS PALSAR images and 21 dual-polarized Sentinel-1 images acquired over San Fernando Valley, CA, USA, and Groningen, The Netherlands, respectively. The application of this method increased the number of coherent pixels by almost a factor of eight compared with a single-polarization channel. This paper concludes that a coherence estimate can be significantly improved by applying scattering property-based adaptive filtering and coherence matrix decomposition and accurate displacement measurements can be achieve