Download or read book Persistent Scatterer Interferometry in Natural Terrain written by Piyush Shanker Agram and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-series InSAR techniques are designed to estimate the temporal characteristics of surface deformation by combining information from multiple SAR images acquired over time. In many cases, these techniques also enable us to measure deformation signals in locations where conventional InSAR fails and also to reduce the error associated with deformation measurements. Among these techniques, Persistent Scatterer (PS) methods work by identifying the ground resolution elements that are dominated by a single scatterer. A persistent scatterer exhibits reduced baseline and temporal decorrelation due to its stable, point-like scattering mechanism. In PS analysis, a set of interferograms formed with a single master scene are processed at single look resolution in order to maximize the signal-to-clutter ratio (SCR) of the resolution elements containing a single dominant scatterer. In urban terrain, buildings and other man-made structures often act as PS due to their corner reflector-like scattering behavior and high radar reflectivity. Hence, traditional SAR amplitude-based PS-InSAR techniques have proved to be very e ffective in urban terrain. In natural terrain, the absence of bright manmade structures makes reliable estimation of deformation using PS-InSAR techniques a challenging task. The main obstacle is in the phase unwrapping stage, where the solutions are directly dependent on the PS network density. We have developed a two pronged approach to improve the applicability of PS-InSAR techniques to natural terrain - increasing PS network density and improving the reliability of phase unwrapping algorithms. We first present an information theoretic approach to PS pixel selection and demonstrate the ability of these new algorithms in identifying a denser network of PS in natural terrain. We then address the spatio-temporal (three dimensional) phase unwrapping problem applicable to sparse and non-uniformly sampled time-series InSAR data sets, and present two novel phase unwrapping algorithms. We demonstrate the efficacy of our new PS selection technique with experimental results from the San Francisco Bay Area, Lyngen region of Norway and the creeping section of the Central San Andreas Fault. We explain the salient features of our new "edgelist" phase unwrapping algorithm with results from the Central San Andreas Fault region north of Park field, CA. We provide detailed comparisons of the estimated line of sight velocity and deformation time-series with results from other time-series InSAR algorithms developed by research groups based in NORUT, Norway and IREA-CNR, Italy.