Offline-Online Change Detection for Sentinel-1 InSAR Time Series

Traditional applications of Interferometric Synthetic Aperture Radar (InSAR) data involved inverting an interferogram stack to determine the average displacement velocity. While this approach has useful in continuously deforming regions, much information is lost by simply fitting a line through time series. Thanks regular acquisitions across most world ESA Sentinel-1 satellite constellation, we are now position explore opportunities for near-real deformation monitoring. In paper present statistical detecting offsets and gradient changes InSAR Our key assumption that 5 years sufficient calculate population standard deviation detection variables. offset detector identifies statistically significant peaks first, second third difference The change movements derivative We exploit high spatial resolution continuity geophysical signals filter out false positive detections arise due signal noise. When combined with processing these detectors, particularly change, could be used detect incipient ground associated phenomena, example from landslides or volcanic eruptions.