Fuzzy Modeling with Spatial Information for Geographic Problems

This book focuses on research advances in approaches for incorporating explicit handling of uncertainty, especially by fuzzy sets, to address geographic problems. §Over the past several years interest in the use of fuzzy sets approaches has grown across a broad spectrum of fields that use spatial information to address geographic problems. Not only has there been considerable research on incorporating fuzzy sets in the geographic information systems (GIS) supporting geographic problem solving, but increasingly the uncertainties inherent in modeling geographic problems have been addressed using soft computing methods.§This book has two aims. One is to stimulate further research in both the theory and application of fuzzy sets to spatial information management and geographic problem solving. The other is to highlight the advances in research which have matured to the point that we find fuzzy modeling being used by geoscientists, computer scientists, geographers, ecologists, engineers, and others. The book includes examples of the use of fuzzy sets in representational issues such as terrain features, landscape morphology, spatial extents and approaches for spatial interpolation. A variety of applications using fuzzy sets are covered including data mining, spatial decision making, ecological simulation, and reliability in GIS.Over recent years, interest in using fuzzy sets approaches has grown across fields that use spatial information in geographic problems. Not only has there been considerable research on fuzzy sets in GIS that support geographic problem solving, but increasingly the uncertainties inherent in modeling geographic problems are addressed using soft-computing methods. This book focuses on research advances in approaches for incorporating explicit handling of uncertainty, especially by fuzzy sets, to address geographic problems. It has two aims: to stimulate research in the theory and application of fuzzy sets to spatial information management and geographic problem solving; and to highlight advances that have matured so much that geoscientists, computer scientists, geographers, et al. use fuzzy modeling. The book includes examples of the use of fuzzy sets in representational issues such as terrain features, landscape morphology, spatial extents and approaches for spatial interpolation, plus applications using fuzzy sets covering data mining, spatial decision making, ecological simulation, and reliability in GIS.