Exploring high repetitivity remote sensing time series for mapping and monitoring natural habitats - A new approach combining OBIA and k-partite graphs

Exploration haute répétitivité séries chronologiques de télédétection pour la cartographie et la surveillance des habitats naturels : une nouvelle approche combinant OBIA et graphes de k-partite

Guttler, F. ; Corbane, C. ; Alleaume, S. ; Ienco, D. ; Poncelet, P. ; Nin, J. ; Teisseire, M.

Type de document
Communication scientifique sans actes
Langue
Anglais
Affiliation de l'auteur
IRSTEA MONTPELLIER UMR TETIS FRA ; IRSTEA MONTPELLIER UMR TETIS FRA ; IRSTEA MONTPELLIER UMR TETIS FRA ; IRSTEA MONTPELLIER UMR TETIS FRA ; UNIVERSITE DE MONTPELLIER II UMR 5506 LIRMM MONTPELLIER FRA ; UNIVERSITAT POLITECNICA DE CATALUNYA BARCELONA ESP ; IRSTEA MONTPELLIER UMR TETIS FRA
Année
2014
Résumé / Abstract
High repetitivity remote sensing could substantially improve natural habitats monitoring and mapping in the next years. However, dense time series of satellite images require new processing methodologies. In this paper we proposed an approach which combines Object Based Image Analysis (OBIA) and k-partite graphs for detecting spatiotemporal evolutions in a Mediterranean protected site composed of several types of natural and semi-natural habitats. The method was applied over a recent dataset (SPOT4 Take-5) specially conceived to simulate the acquisition frequency of the future Sentinel-2 satellites. The results indicate our method is capable to synthesize complex spatiotemporal evolutions in a semi-automatic way, therefore offering a new tool to analyze high repetitivity satellite time series.
Congrès
IGARSS, 13/07/2014 - 18/07/2014, Québec, CAN

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