SITS-P2miner

Extract and explore GFS-patterns!

SITS-P2miner: for extracting and ranking maximal Grouped Frequent Sequential patterns (GFS-patterns) from Satellite Image Times Series (SITS). It includes SPATPAM and also implements our latest ranking procedures (swap randomization, normalized mutual information). A quantization procedure (equal frequency bucketting) and a pattern clustering module (hierarchical, Levenshtein distance) are embodied. A full running example is made available. It relies on an NDVI SITS kindly provided by Rémi Andreoli (Bluecham SAS).

Authors: Nicolas Méger (LISTIC), Christophe Rigotti (LIRIS), Andreea Julea (European Commission-Joint Research Centre), Felicity Lodge, Quentin Chalabi, Hoang Viet Tuan Nguyen (LISTIC, LIRIS), Aymeric Gaillard, Clément Bois, Olivier Bal-Petre.

SITS-P2miner: Pattern-Based Mining of Satellite Image Time Series. Tuan Nguyen, Nicolas Méger, Christophe Rigotti, Catherine Pothier, Rémi Andréoli. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) Demo, Sep 2016, Riva del Garda, Italy. pp.63-66, 2016.