SPATIO-TEMPORAL OBJECT STABILITY FOR MONITORING EVOLVING AREAS IN SATELLITE IMAGE TIME SERIES
Monitoring observable processes in Satellite Image Time Series (SITS) is one of the crucial way to understand dynamics of our planet that is facing unexpected behaviors due to climate change. In this paper, we propose a novel method to assess the evolution of objects (and especially their surface) through time. To do so, we first build a space-time tree representation of image time series. The so-called space-time tree is a hierarchical representation of an image sequences into a nested set of nodes characterizing the observed regions at multiple spatial and temporal scales. Then, we measure for each node the spatial area occupied at each time sample, and we focus on its evolution through time. We thus define the spatio-temporal stability of each node. We use this attribute to identify and measure changing areas in a remotely-sensed scene. We illustrate the purpose of our method with some experiments in a coastal environment using Sentinel-2 images, and in a flood occurred area with Sentinel-1 images.