Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1109/36.992798
Title (Primary) Fuzzy rule-based classification of remotely sensed imagery
Author Bárdossy, A.; Samaniego, L. ORCID logo
Source Titel IEEE Transactions on Geoscience and Remote Sensing
Year 2002
Department CHS
Volume 40
Issue 2
Page From 362
Page To 374
Language englisch
Keywords fuzzy classification; land cover; remote sensing; simulated annealing
Abstract The purpose of this paper is to investigate the applicability of fuzzy rule-based modeling to classify a LANDSAT TM scene from 1984 of an area located in the south of Germany. Both a land cover map with four different categories and an image depicting the degree of ambiguity of the classification for each pixel is the expected output. The fuzzy classification algorithm will use a rule system derived from a training set using simulated annealing as an optimization algorithm. The results are then validated and compared with a common classification method in order to judge the effectiveness of the proposed technique. It will also be shown that the proposed method with only nine rules for four different land cover classes performs slightly better than the maximum likelihood classifier (MLC). For error assessment, the traditional error matrix and fuzzy operators have been used.
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Bárdossy, A., Samaniego, L. (2002):
Fuzzy rule-based classification of remotely sensed imagery
IEEE Trans. Geosci. Remote Sensing 40 (2), 362 - 374 10.1109/36.992798