Abstract
Thematic maps of spatial data are constructed by using standard thematic classification methods that do not allow management of the uncertainty of classification and, consequently, evaluation of the reliability of the resulting thematic map. We propose a novel fuzzy-based thematic classification method applied to construct thematic maps in Geographical Information Systems. An initial fuzzy partition of the domain of the features of the spatial dataset is constructed using triangular fuzzy numbers; our method finds an optimal fuzzy partition evaluating the fuzziness of the fuzzy sets by using a fuzzy entropy measure. An assessment of the reliability of the final thematic map is performed according to the fuzziness of the fuzzy sets. We implement our method on a GIS framework, testing it on various vector and image spatial datasets. The results of these tests confirm that our thematic classification method provide thematic maps with a higher reliability with respect to that obtained through fuzzy partitions constructed by expert users.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference23 articles.
1. Schowengerdt, R.A. Chapter 9—Thematic Classification. Remote Sensing (Third Edition), 2007.
2. The Data Model Concept in Statistical Mapping;Jenks;Int. Yearb. Cartogr.,1967
3. The principle of fuzzy mathematical multilayer synthetic evaluation and its application of quality evaluation in thematic mapping;He;Acta Geod. Cartogr. Sin.,1989
4. Evaluating the classification accuracy of fuzzy thematic maps with a simple parametric measure;Ricotta;Int. J. Remote Sens.,2004
5. Iδ-Index, A Measure of Dispersion of Individuals;Morisita;Res. Popul. Ecol.,1962