Monitoring urban sprawl from Satellite Image Time Series

Satellite Image Time Series are becoming increasingly available and will continue to do so in the coming years thanks to the launch of space missions which aim at providing a coverage of the Earth every few days with high spatial resolution. In the case of optical imagery, it will be possible to produce land use and cover change maps with detailed nomenclatures. It has been shown that the Dynamic Time Warping (DTW) similarity measure makes it possible to compare radiometric time series with different lengths and sampling. This work aims at showing that DTW is also able to capture distorted phenomena sensed over a long satellite image time series. This article details the analysis of a satellite image time series sensed over 20 years; we show that DTW makes it possible to extract static phenomena, as well as distorted ones such as urbanized areas.