Extracting characteristics of Satellite Image Time Series with Decision Trees

Thomas Guyet 1, 2
1 DREAM - Diagnosing, Recommending Actions and Modelling
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : The use of SITS improves the accuracy of the mapping of landcover. Nonetheless, SITS are complex datasets and the classification algorithm may be difficult to set up. In this article, we propose to learn an explicit model, a decision tree, from labelled time series. Our decision trees model enables to identify which time series and which time periods are the most discriminant for a classification task and thus, it provides insightful knowledge to the expert. We illustrate this method with the characterisation of agro-ecological areas of the Senegal.
Type de document :
Communication dans un congrès
MultiTemp, 2015, Annecy, France. IEEE, pp.260-263, Proceedings of the MultiTemp Workshop. 〈http://www.multitemp2015.org/〉
Liste complète des métadonnées

https://hal.inria.fr/hal-01178943
Contributeur : Thomas Guyet <>
Soumis le : mardi 21 juillet 2015 - 12:38:23
Dernière modification le : mercredi 16 mai 2018 - 11:23:02

Identifiants

  • HAL Id : hal-01178943, version 1

Citation

Thomas Guyet. Extracting characteristics of Satellite Image Time Series with Decision Trees. MultiTemp, 2015, Annecy, France. IEEE, pp.260-263, Proceedings of the MultiTemp Workshop. 〈http://www.multitemp2015.org/〉. 〈hal-01178943〉

Partager

Métriques

Consultations de la notice

337