Investigating Persistent and Distributed Scatterers to Better Resolve Low Amplitude Deformation with InSAR in Vegetated Terrains

Tuesday, 16 December 2014
Xiaopeng Tong and David A Schmidt, University of Washington, Seattle, WA, United States
Multi-temporal InSAR methods are successful at revealing low amplitude surface deformation by reducing the noise from the atmosphere and the Digital Elevation Model (DEM). The Persistent Scatters (PS) InSAR and Small baseline (SBAS) methods are used widely by the InSAR community. However, it is still challenging to recover low deformation rates in highly vegetated mountainous areas.

Our goal is to explore different approaches to identifying PS or stable Distributed Scatterers (DS) for multi-temporal InSAR processing. We are investigating the following methods: 1) amplitude dispersion (Ferretti et al., 2001); 2) average correlation; 3) spatial correlation of phase (Hooper et al., 2004); 4) comparison of phase against a known mathematical model (Shanker and Zebker, 2007); 5) statistical analysis of the coherence matrix (Ferretti et al., 2011); 6) polarimetric bounce characteristics. We first align the SAR images to form a stack of Single Look Complex (SLC) using “batch processing”. We work with this 3-dimensional SLC stack to identify high-quality PS and DS using the aforementioned methods. Next we design a filter based on the characteristics of the scatterers to form interferograms. This comparative study on identifying and filtering PS and DS can be integrated with interferogram stacking or time-series approaches like PSInSAR, SBAS or wavelet-based methods.

We are working with the ERS-1, ERS-2 and ALOS-1 SAR data to study landslides and volcano deformation over various terrains in the Cascade Range. From these observations we will be able to construct better physical models to explain various deformation processes.