Persistent Scatterer Density by Image Resolution and Terrain Type

Abstract

Persistent scatterer interferometry is a powerful time-series technique which uses the most temporally stable pixels (denoted persistent scatterers, or PS), to enable measurement of deformation in decorrelation-prone data sets. System performance depends heavily on the density of identified PS, which is influenced by two factors: image resolution and terrain type. In this work, we establish a quantitative link between PS density and these factors. First, we present a simple theoretical framework for predicting PS density by estimating the change in the pixel signal-to-clutter ratio (SCR) as a function of bandwidth for several different terrain types. Then, we analyze the behavior of PS density for three terrain types at different image resolutions. The model agrees with empirical results within 50% error, and rather closer for the high SCR points that form the desired network of PS points. Additionally, we find that the probability density functions of PS occurrence with respect to SCR for each region are approximately independent of system bandwidth. Thus, the increase in PS density is roughly proportional to increased bandwidth due to a higher pixel density in finer resolution images. We note that there is a slight increase in PS detectability with increasing bandwidth beyond the bandwidth scaling, but the gain is small compared to the bandwidth factor. These results form a model with a more quantitative understanding of the relationship between PS density and by extension, PS system performance, and image resolution and terrain.