Abstract
Persistent scatterer (PS) techniques are a set of important time-series tools for interferometric synthetic aperture radar (InSAR) that enable deformation analysis in highly decorrelated terrain. Detailed knowledge of the statistics of persistent scatterers in InSAR images is critical for the design of better techniques that will enable both the extraction of deformation in traditionally difficult regions as well as develop a better understanding of how performance of these algorithms relates to important system parameters. In this article, we characterize the backscatter statistics of both persistent and distributed scatterers over wavelength using data from X -band (COSMO-SkyMed), C -band (Sentinel-1), and L -band (ALOS) sensors. We show that popular distributions that have previously been used to fit SAR backscatter can effectively capture the returns from both PS and clutter, with the $\text {G}^0$ distribution being the most applicable across wavelength and scatterer type. Thus, our work paves the way for improved detection algorithms to be designed based on these distributions and also builds an initial foundation for developing a greater theoretical understanding of PS statistics.
Highlights
I NTERFEROMETRIC synthetic aperture radar (InSAR) has become an increasingly popular remote sensing tool for geophysical and earth-observing studies [1], [2]
The initial fits for Persistent scatterer (PS) and clutter probability distributions for each wavelength at full bandwidth are plotted in Fig. 2, displayed on a log scale
The K distribution provides a good fit to the PS backscatter at X- and L-band and the clutter backscatter at L-band, while the lognormal better fits the PS backscatter at C-band and the clutter at X- and C-bands
Summary
I NTERFEROMETRIC synthetic aperture radar (InSAR) has become an increasingly popular remote sensing tool for geophysical and earth-observing studies [1], [2]. InSAR studies of many important natural regions, such as forested and vegetated terrain, are often still limited due to difficulties in extracting reliable deformation signals in areas that suffer from high decorrelation [4]. PSs are temporally stable pixels in an InSAR image that can be used to form a reliable network of points which can be used for analysis. By applying this technique, we can analyze ground deformation of several millimeters in areas that otherwise suffer from high decorrelation. Such research and a suitable theoretical framework are needed for the design of increasingly accurate and analytically sound detection methods, which in turn would result in a denser network of reliable measurements that enable more detailed deformation analysis. We discuss possible other factors that may contribute to differing observed statistics by satellite, and we conclude with general observations and suggestions for steps
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
