Spatiotemporal Change Detection Based on Persistent Scatterer Interferometry: A Case Study of Monitoring Building Changes

Abstract

Persistent scatterer interferometry (PSI) detects and analyses PS points from multitemporal SAR images for scene deformation monitoring. We propose a novel technique to identify disappearing and emerging PS points, which are regarded as building changes in cities. A spatiotemporal analysis is implemented as both spatial position and occurrence time are obtained for each change point. We first estimate each pixel's temporal coherences in different image subsets. Computed from temporal coherences, a change index sequence is introduced to quantify each pixel's probabilities of being change points at different times. All pixels' change indices are then utilized to extract change points by a global, automatic, and statistical-based scheme. We then eliminate blunders by a spatial filtering. Finally, the occurrence times of the change points are detected based on the temporal variation in their change index sequences. We implement a simulated data test to validate and assess our method. Using TerraSAR-X images, our real data test successfully recognizes steady, disappearing, and emerging buildings in Berlin, Germany within 2013.