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Proceedings Paper

Combination of fuzzy sets and Dempster-Shafer theories in forest map updating using multispectral data
Author(s): Francois Leduc; Basel Solaiman; Francois Cavayas
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Paper Abstract

This paper explains a new approach to change detection and interpretation in a context of forest map updating. In this temporal change analysis we use data set composed of map at time T0 and a satellite image at time T1 and we refer to this as a mixed fusion approach. The analysis of remotely sensed data always necessitates the use of approximate reasoning. For this purpose, we use fuzzy logic to evaluate the objects' membership values to the considered classes and the Dempster-Shafer theory to analyze the confusion between the classes and to find the more evident class to which an object belongs.

Paper Details

Date Published: 22 March 2001
PDF: 12 pages
Proc. SPIE 4385, Sensor Fusion: Architectures, Algorithms, and Applications V, (22 March 2001); doi: 10.1117/12.421120
Show Author Affiliations
Francois Leduc, Ecole Nationale Superieure des Telecommunications de Bretagne and Univ. de Montreal (Canada)
Basel Solaiman, Ecole Nationale Superieure des Telecommunications de Bretagne (France)
Francois Cavayas, Univ. de Montreal (Canada)


Published in SPIE Proceedings Vol. 4385:
Sensor Fusion: Architectures, Algorithms, and Applications V
Belur V. Dasarathy, Editor(s)

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