Fuzzy Modeling with Spatial Information for Geographic Problems

ISBN-13: 9783540237136 / Angielski / Twarda / 2005 / 338 str.

Frederick E. Petry;Vincent B. Robinson;Maria A. Cobb

Opis

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.

Recenzje

From the reviews:

"Fuzzy Modelling ... is a collection of papers of diverse but interrelated topics on the use of fuzzy logic ... . The reader is given enough information and references ... . this book will provide an excellent background on fuzzy logic and how it can be applied to a variety of spatial problems. It is also a valuable information source for professors, graduate students or industry professionals, and it should be on their bookshelves or at least in the library." (Alvin Simms, Geomatica, Vol. 60 (4), 2006)

Spis treści

Reasoning About Regions, Relations, and Fields.- Fuzzy Reasoning about Geographic Regions.- Combined Extraction of Directional and Topological Relationship Information from 2D Concave Objects.- Field Based Methods for the Modeling of Fuzzy Spatial Data.- Modeling Localities with Fuzzy Sets and GIS.- Fuzzy Classification.- Mining Weather Data Using Fuzzy Cluster Analysis.- Modelling the Fuzzy Spatial Extent of Geographical Entities.- Multi-Dimensional Interpolations with Fuzzy Sets.- Talking Space — A Social & Fuzzy Logical GIS Perspective On Modelling Spatial Dynamics.- A Valuation of the Reliability of a GIS Based on the Fuzzy Logic in a Concrete Case Study.- Fuzzy Representations of Landscape Features.- Fuzziness and Ambiguity in Multi-Scale Analysis of Landscape Morphometry.- Fuzzy Representation of Special Terrain Features Using a Similarity-based Approach.- Decision Making with GIS and Fuzzy Sets.- Spatial Decision-Making Using Fuzzy Decision Tables: Theory, Application and Limitations.- Spatial Decision Making Using Fuzzy GIS.- Spatially Explicit Individual-Based Ecological Modeling with Mobile Fuzzy Agents.

Blurb

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.