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On the use of ancillary data by applying the concepts of the theory of evidence to remote sensing digital image classification

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In this study we investigate a new approach to implement concepts developed by the 'theory of evidence' to remote sensing digital image classification. In the proposed approach, auxiliary variables are structured as layers in a Geographical Information System (GIS)-like format to produce layers of belief and plausibility. Thresholds are applied to the layers of belief and plausibility to detect errors of commission and omission, respectively on the thematic image. The thresholds are estimated as functions of the user's and producer's accuracy. Preliminary tests were performed over an area covered by natural forest with Araucaria, showing some promising results.
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Document Type: Research Article

Affiliations: Federal University at Rio Grande do Sul - UFRGS, Center for Remote Sensing, CP 15052 - Porto, Alegre, RS, Brazil

Publication date: April 1, 2010

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