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Fuzzy set approach to assessing similarity of categorical maps

Hagen, A (2003) Fuzzy set approach to assessing similarity of categorical maps International Journal of Geographical Information Science, 17 (3). pp. 235-249.

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Abstract

For the evaluation of results from remote sensing and high-resolution spatial models it is often necessary to assess the similarity of sets of maps. This paper describes a method to compare raster maps of categorical data. The method applies fuzzy set theory and involves both fuzziness of location and fuzziness of category. The fuzzy comparison yields a map, which specifies for each cell the degree of similarity on a scale of 0 to 1. Besides this spatial assessment of similarity also an overall value for similarity is derived. This statistic corrects the cell-average similarity value for the expected similarity. It can be considered the fuzzy equivalent of the Kappa statistic and is therefore called KFuzzy. A hypothetical case demonstrates how the comparison method distinguishes minor changes and fluctuations within patterns from major changes. Finally, a practical case illustrates how the method can be useful in a validation process.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Civil and Environmental Engineering
Authors :
NameEmailORCID
Hagen, AUNSPECIFIEDUNSPECIFIED
Date : 2003
Identification Number : 10.1080/13658810210157822
Copyright Disclaimer : This is an Author's Accepted Manuscript of an article published in International Journal of Geographical Information Science 2003, copyright Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/13658810210157822
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 09 Aug 2013 15:32
Last Modified : 07 Jul 2017 15:10
URI: http://epubs.surrey.ac.uk/id/eprint/790273

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