Detection and Interpretation of Change in Registered Satellite Image Time Series
Tristan Dagobert, Rafael Grompone von Gioi, Carlo de Franchis, Charles Hessel
⚠ This is a preprint. It may change before it is accepted for publication.


Time series of satellite images are now massively available thanks to the existence of several constellations of recurrent satellites. We propose a method for detecting and measuring the duration of changes on such series. This approach is intended to be generic and independent of the type of satellite used, whether band limited or multispectral. It is based on a global analysis of the sequence. The statistical detection method is applied to a residual sequence computed from backward and forward novelty filters applied to all images in the series. Significant changes are computed with a guarantee on their number of false alarms (NFA). To establish the efficiency of the method, we have created an open database of 28 sequences of 20 images acquired by the Sentinel-2 satellite, in different regions of the world. We obtain satisfactory results which are consistent with the visual observations.