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

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

6 Citas (Scopus)

Resumen

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 originalInglés
Título de la publicación alojadaInternational Geoscience and Remote Sensing Symposium (IGARSS)
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas3930-3933
Número de páginas4
ISBN (versión digital)9781479957750
DOI
EstadoPublicada - 4 nov 2014
Publicado de forma externa
EventoJoint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014 - Quebec City, Canadá
Duración: 13 jul 201418 jul 2014

Serie de la publicación

NombreInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conferencia

ConferenciaJoint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014
País/TerritorioCanadá
CiudadQuebec City
Período13/07/1418/07/14

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