Combination of fuzzy sets and Dempster-Shafer theories in forest map updating using multispectral data

Francois Leduc; Basel Solaiman; Francois Cavayas

doi:10.1117/12.421120

22 March 2001 Combination of fuzzy sets and Dempster-Shafer theories in forest map updating using multispectral data

Francois Leduc, Basel Solaiman, Francois Cavayas

Proceedings Volume 4385, Sensor Fusion: Architectures, Algorithms, and Applications V; (2001) https://doi.org/10.1117/12.421120
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

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.

Citation Download Citation

Francois Leduc, Basel Solaiman, and Francois Cavayas "Combination of fuzzy sets and Dempster-Shafer theories in forest map updating using multispectral data", Proc. SPIE 4385, Sensor Fusion: Architectures, Algorithms, and Applications V, (22 March 2001); https://doi.org/10.1117/12.421120

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