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A new approach to selecting coherent pixels for ground-based SAR deformation monitoring

Lookup NU author(s): Professor Zhenhong Li, Professor Jon Mills

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

Ground-Based Synthetic Aperture Radar (GBSAR) is a flexible field-based remote sensing technology that, together with interferometric SAR (InSAR), has proven to be a powerful and effective tool for deformation monitoring. The Small Baseline Subset (SBAS) algorithm represents a typical advanced InSAR technique that extracts distributed scatterers from a network of interferogramsfor the measurement of time series displacement. However, it is well known that coherent points are variable from one interferogram to another, which renders time series analysis complicated. This study therefore proposes an effective approach to selecting coherent pixels from a network of interferograms, aiming to maximize the density of selected pixels and optimize the reliability of GBSAR time series analysis. A pixel is selected for the entire analysis if its coherent phase is capable of forming a full-rank coefficient matrix in the network inversion. A full-rank matrix means the pixel-dependent subset network is connected. Combining with the accurate estimation of coherence and interferometric phase based on sibling pixels identified from non-local windows, the proposed approach enables the selection of not only qualified partially coherent pixels but also persistent scatterers. The proposed approach has been incorporated into a bespoke GBSAR time series analysis chain for deformation monitoring, from which a mean velocity map, displacement time series and atmospheric phase delays can be determined. To validate the approach, experiments on two GBSAR datasets were performed. In both studies, sufficient coherent pixels were selected, suggesting the feasibility of the proposed coherent pixel selection algorithm. Displacement time series at the level of a few sub-millimeters were observed for both datasets, indicating the feasibility of the newly-developed GBSAR time series analysis chain for deformation monitoring, which is believed to lead to a wide range of scientific and practical applications.


Publication metadata

Author(s): Wang Z, Li Z, Mills JP

Publication type: Article

Publication status: Published

Journal: ISPRS Journal of Photogrammetry and Remote Sensing

Year: 2018

Volume: 144

Pages: 412-422

Print publication date: 01/10/2018

Online publication date: 17/08/2018

Acceptance date: 08/08/2018

Date deposited: 08/09/2018

ISSN (print): 0924-2716

ISSN (electronic): 1872-8235

Publisher: Elsevier BV

URL: https://doi.org/10.1016/j.isprsjprs.2018.08.008

DOI: 10.1016/j.isprsjprs.2018.08.008


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