A Fuzzy Entropy-Based Thematic Classification Method Aimed at Improving the Reliability of Thematic Maps in GIS Environments

Thematic maps of spatial data are constructed by using standard thematic classification methods that do not allow management the uncertainty and, consequently, evaluation reliability resulting map. We propose a novel fuzzy-based method applied to construct in Geographical Information Systems. An initial fuzzy partition domain features dataset is triangular numbers; our finds an optimal evaluating fuzziness sets entropy measure. assessment final map performed according sets. implement on GIS framework, testing it various vector and image datasets. The results these tests confirm provide with higher respect obtained through partitions expert users.