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

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

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

6 Cites (Scopus)

Resum

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.

Idioma originalAnglès
Títol de la publicacióInternational Geoscience and Remote Sensing Symposium (IGARSS)
EditorInstitute of Electrical and Electronics Engineers Inc.
Pàgines3930-3933
Nombre de pàgines4
ISBN (electrònic)9781479957750
DOIs
Estat de la publicacióPublicada - 4 de nov. 2014
Publicat externament
EsdevenimentJoint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014 - Quebec City, Canada
Durada: 13 de jul. 201418 de jul. 2014

Sèrie de publicacions

NomInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conferència

ConferènciaJoint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014
País/TerritoriCanada
CiutatQuebec City
Període13/07/1418/07/14

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