Towards efficient satellite time series analysis: combination of Dynamic Time Warping and Quasi-Flat Zones

Jonathan Weber (1) , François Petitjean (2) , Pierre Gancarski (2)

1 QGAR - Querying Graphics through Analysis and Recognition
2 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection

Satellite Image Time Series (SITS, for short) are useful resources for Earth monitoring. Upcoming satellites will provide a global coverage of the Earth's surface with a short revisit time (five days); a huge amount of data to analyze will be produced. In order to be able to analyze efficiently and accurately these images, new methods have to be designed. In this article, we propose to combine a spatio-temporal segmentation pre-processing method - quasi-flat zones, which have been recently extended to video analysis - and the distortion power of DTW to simplify the representation of the SITS, in order to reduce both the time and the memory consumption. Experiments carried out on a series of 46 images show that the memory consumption can be reduced by an order of magnitude without reducing the relevance of the analysis.

Jonathan Weber, François Petitjean, Pierre Gancarski. Towards efficient satellite time series analysis: combination of Dynamic Time Warping and Quasi-Flat Zones. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2012, Munich, Germany. pp.4387-4390, ⟨10.1109/IGARSS.2012.6350401⟩. ⟨hal-00761291⟩