Application of Anomalous Change Detection for Identifying Changes in InSAR Time Series

Satellite interferometric synthetic aperture radar (InSAR) is an advanced geodetic technique capable of measuring surface deformation on the order of centimeters over large spatial footprints (e.g., tens to hundreds of kilometers). While InSAR is advantageous for remotely detecting subtle surface changes, true deformation signals are often obscured by noise contributions from topography and atmospheric effects. We develop a method to identify changes in InSAR time series (TS) deformation rate maps amidst noise using anomalous change detection (ACD) techniques. We focus on identifying anomalies from three types of changes: permanent, persistent, and transient, and we develop our method based on four ground truth test sites that reflect those change event types. We find that chronochrome ACD applied to successive 3-month interval InSAR TS deformation rate maps performs the best, especially when combined with ACD-based InSAR noise mitigation techniques.