Mining pixel evolutions in satellite image time series for agricultural monitoring

Authors:
Andreea Julea;Nicolas Méger;Christophe Rigotti;Emmanuel Trouvé;Philippe Bolon;Vasile Lăzărescu
Affiliations:
Institute for Space Sciences, Bucharest-Măgurele, Romania;Université de Savoie, Polytech'Savoie, LISTIC Laboratory, Annecy-le-Vieux Cedex, France;Université de Lyon, CNRS, INSA-Lyon, LIRIS, UMR 5205, France;Université de Savoie, Polytech'Savoie, LISTIC Laboratory, Annecy-le-Vieux Cedex, France;Université de Savoie, Polytech'Savoie, LISTIC Laboratory, Annecy-le-Vieux Cedex, France;Politehnica University of Bucharest, Faculty for Electronics, and Information Engineering Department, Romania
Venue:
ICDM'11 Proceedings of the 11th international conference on Advances in data mining: applications and theoretical aspects
Year:
2011

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Abstract

In this paper, we present a technique to help the experts in agricultural monitoring, by mining Satellite Image Time Series over cultivated areas. We use frequent sequential patterns extended to this spatiotemporal context in order to extract sets of connected pixels sharing a similar temporal evolution. We show that a pixel connectivity constraint can be partially pushed to prune the search space, in conjunction with a support threshold. Together with a simple maximality constraint, the method reveals meaningful patterns in real data.