Spatio-Temporal Stability Analysis in Satellite Image Times Series
Mohamed Chelali, Camille Kurtz, Anne Puissant, Nicole Vincent
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Abstract
Satellite Image Time Series (SITS) provide valuable information for the study of the Earth’s surface. In particular, this information may improve the comprehension, the understanding and the mapping of many phenomenons such as earthquake monitoring, urban sprawling or agricultural practices. In this article, we propose a method to define new spatio-temporal features from SITS based on the measure of the temporal stability. The proposed method is based on a compression algorithm named Run Length Encoding leading to a novel image representation from which stability features can be measured. Such features can then be used in several applications such as SITS summarizing, to make easier the interpretation of such a data-cube, or the classification of spatio-temporal patterns. The preliminary results obtained from a series of 50 Sentinel-2 optical images highlight the interest of our approach in a remote sensing application.