Fuzzy Sets Approach to Spatial Analysis

Abstract

Since its inception, fuzzy sets theory has been extensively developed and applied to the analysis and solution of complex problems in a large variety of disciplines. Human behavior in space is highly complex and is intrinsically imprecise. Modeling human systems with classical mathematics generally lead to a mechanical analysis and prediction of behavior in space and time. To capture more appropriately imprecise human behavior as well as spatial structures and processes, we need a theoretical paradigm which deals directly with complexity and imprecision in a formal manner. Over the years, fuzzy sets theory in general and fuzzy logic in particular have been successfully developed and applied to solve fundamental problems in spatial analysis. In this paper, I give a state-of-the-art examination of the fuzzy sets approach to spatial analysis. It covers the approximate characterization of imprecise spatial concepts, regional conceptualization and regionalization, spatial preference and equilibrium analysis, spatial optimization, spatial information systems and spatial decision support systems. I also outline in the end plausible directions for further research, particularly the integrative development with other new paradigms for spatial analysis.KeywordsGeographic Information SystemSpatial AnalysisLinguistic VariableFuzzy SubsetFuzzy IdealThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.