TY - GEN
T1 - Exploring high repetitivity remote sensing time series for mapping and monitoring natural habitats - A new approach combining OBIA and k-partite graphs
AU - Guttler, F.
AU - Alleaume, S.
AU - Corbane, C.
AU - Ienco, D.
AU - Nin, J.
AU - Poncelet, P.
AU - Teisseire, M.
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/4
Y1 - 2014/11/4
N2 - 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.
AB - 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.
KW - Natural habitats monitoring
KW - OBIA
KW - SPOT4 Take-5
KW - graph representation
KW - remote sensing time series
UR - http://www.scopus.com/inward/record.url?scp=84911418485&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2014.6947344
DO - 10.1109/IGARSS.2014.6947344
M3 - Conference contribution
AN - SCOPUS:84911418485
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 3930
EP - 3933
BT - International Geoscience and Remote Sensing Symposium (IGARSS)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Joint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014
Y2 - 13 July 2014 through 18 July 2014
ER -