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Proceedings Paper

Capabilities of ERS sensors for Mediterranean vegetation detection using multitemporal data
Author(s): Guillem Chust; Danielle Ducrot; Jerome Bruniquel; Joan Lluis Pretus
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Paper Abstract

The objective of the present study is to evaluate the performances of a series of SAR ERS images for a land cover classification of a Mediterranean landscape, focusing on the discrimination of vegetation types. We tested the contribution of multitemporal data and contextual methods of classification with and without filtering for land cover discrimination. An index of temporal change was developed to characterise the stability of land covers, this index is based on the mean normalised difference between consecutive dates. This study shows the importance of time series of ERS sensor and of the vectorial MMSE filter based on segmentation, for land cover classification. Fifteen land cover classes, where eight of them concern to different vegetation types, have been classified obtaining a 80.1 % of mean producer’s accuracy for 1998 series, and 70.6 % for 1994. These results are comparable with those from two-date SPOT images (85.3 % of mean producer’s accuracy).

Paper Details

Date Published: 21 December 2000
PDF: 12 pages
Proc. SPIE 4173, SAR Image Analysis, Modeling, and Techniques III, (21 December 2000); doi: 10.1117/12.410659
Show Author Affiliations
Guillem Chust, Ctr. d'Etudes Spatiales de la Biosphere (France), Univ. de Barcelona (Spain), and Institut (Spain)
Danielle Ducrot, Ctr. d'Etudes Spatiales de la Biosphere (France)
Jerome Bruniquel, Alcatel Space Industries (France)
Joan Lluis Pretus, Univ. de Barcelona (Spain)

Published in SPIE Proceedings Vol. 4173:
SAR Image Analysis, Modeling, and Techniques III
Francesco Posa; Luciano Guerriero, Editor(s)

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