Efficient Satellite Image Time Series Analysis Under Time Warping

Francois Petitjean 1 Jonathan Weber 2
2 QGAR - Querying Graphics through Analysis and Recognition
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Earth observation satellites are now providing images with short revisit cycle and high spatial resolution. The amount of produced data requires new methods that will give a sound temporal analysis while being computationally efficient. Dynamic time warping has proved to be a very sound measure to capture similarities in radiometric evolutions. In this letter, we show that its nonlinear distortion behavior is compatible with the use of a spatiotemporal segmentation of the data cube that is formed by a satellite image time series (SITS). While dealing with spatial and temporal dimensions of SITS at the same time had already proven to be very challenging, this letter proves that, by taking advantage of the spatial and temporal connectivities, both the performance and the quality of the analysis can be improved. Our method is assessed on a SITS of 46 Formosat -2 images sensed in 2006, with an average cloud cover of one third. We show that our approach induces the following: 1) sharply reduced memory usage; 2) improved classification results; and 3) shorter running time.
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Article dans une revue
IEEE Geoscience and Remote Sensing Letters, IEEE - Institute of Electrical and Electronics Engineers, 2014, 11 (6), pp.1143 - 1147. 〈10.1109/LGRS.2013.2288358〉
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https://hal.inria.fr/hal-00940767
Contributeur : Jonathan Weber <>
Soumis le : dimanche 2 février 2014 - 19:48:41
Dernière modification le : mardi 24 avril 2018 - 13:28:52

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Francois Petitjean, Jonathan Weber. Efficient Satellite Image Time Series Analysis Under Time Warping. IEEE Geoscience and Remote Sensing Letters, IEEE - Institute of Electrical and Electronics Engineers, 2014, 11 (6), pp.1143 - 1147. 〈10.1109/LGRS.2013.2288358〉. 〈hal-00940767〉

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