Members
Overall Objectives
Research Program
Application Domains
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New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: Partnerships and Cooperations

National Initiatives

ACASSYA : Supporting the agro ecological evolution of breeding systems in coastal watersheds

Participants : Marie-Odile Cordier, Véronique Masson, René Quiniou.

The Acassya project (ACcompagner l'évolution Agro-écologique deS SYstèmes d'élevage dans les bassins versants côtiers) is funded by ANR/ADD . It started at the beginning of 2009 and will end in June 2013. The main partners are our colleagues from Inra (Sas from Rennes. One of the objectives is to develop modeling tools supporting the management of ecosystems, and more precisely the agro ecological evolution of breeding systems in coastal watersheds. In this context, the challenge is to transform existing simulation tools (as Sacadeau or TNT2 into decision-aid tools, able to answer queries or scenarios about the future evolution of ecosystems. (http://tinyurl.com/ptzdqo5 )

Asterix : spatio-temporal analysis of remote sensing images

Participant : Thomas Guyet.

The Asterix project (Analyse Spatio­-temporelle pour la Télédétection de l'Environnement par Reconnaissance dans les Images compleXes) is funded by ANR/JCJC . The project leader is S. Lefèvre from the IRISA/Vannes Team Obelix. The other partners are OSUR/University of Rennes-2, the Laboratory Image, Ville, Environnement (LIVE), University of Strasbourg, DYNAFOR (INRA/ENSAT), Toulouse and Institut de Physique du Globe de Strasbourg (IPGS), University of Strasbourg. The project started at the end of 2013 (http://anr-asterix.irisa.fr/ ) and will end in 2017.

The goal of the Asterix project is to provide methods, algorithms and software in the field of image analysis and machine learning/data mining to support the analysis of remote sensing images. The project addresses the specific issues of such data: dimensionality, heterogeneity, volume, spatio-temporal nature and the temporal evolution. It is dedicated to the field of environmental remote sensing and deals with concrete applications such as the evolution of the coastline or the colonization of grasslands by ash.

Our contribution to this project will be the proposition of data mining algorithms to deal with the spatio-temporal dimensions of satellite image time series.