Overview
- Editors:
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Frederick E. Petry
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Dept. of Electrical Engineering and Computer Science, Tulane University, New Orleans, USA
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Vincent B. Robinson
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Dept. of Geography, University of Toronto at Mississauga, Mississauga, Canada
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Maria A. Cobb
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Dept. of Computer Science and Statistics, University of Southern Mississippi, Hattiesburg, USA
- First book collecting a broad spectrum of research on geographic information uncertainty using Fuzzy Modeling
- Includes supplementary material: sn.pub/extras
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Table of contents (14 chapters)
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Reasoning About Regions, Relations, and Fields
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- Pascal Matsakis, Dennis Nikitenko
Pages 15-40
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- Jörg Verstraete, Guy De Tré, Rita De Caluwe, Axel Hallez
Pages 41-69
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- Sungsoon Hwang, Jean-Claude Thill
Pages 71-104
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Fuzzy Classification
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- Cidália Costa Fonte, Weldon A. Lodwick
Pages 121-142
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- Susanne Kratochwil, Josef Benedikt
Pages 159-184
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- Ferdinando Di Martino, Vincenzo Loia, Salvatore Sessa, Michele Giordano
Pages 185-208
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Fuzzy Representations of Landscape Features
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- Peter Fisher, Jo Wood, Tao Cheng
Pages 209-232
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- Xun Shi, A-Xing Zhu, Rongxun Wang
Pages 233-251
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Decision Making with GIS and Fuzzy Sets
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- Frank Witlox, Ben Derudder
Pages 253-274
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- Ashley Morris, Piotr Jankowski
Pages 275-298
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- Vincent B. Robinson, Phil A. Graniero
Pages 299-334
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Back Matter
Pages 335-337
About this book
The capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our need to model and manipulate our knowledge of the geophysical world, using compatible representations, is also rapidly increasing. In response to this one fundamental issue of great concern in modern geographical research is how to most effectively capture the physical world around us in systems like geographical information systems (GIS). Making this task even more challenging is the fact that uncertainty plays a pervasive role in the representation, analysis and use of geospatial information. The types of uncertainty that appear in geospatial information systems are not the just simple randomness of observation, as in weather data, but are manifested in many other forms including imprecision, incompleteness and granularization. Describing the uncertainty of the boundaries of deserts and mountains clearly require different tools than those provided by probability theory. The multiplicity of modalities of uncertainty appearing in GIS requires a variety of formalisms to model these uncertainties. In light of this it is natural that fuzzy set theory has become a topic of intensive interest in many areas of geographical research and applications This volume, Fuzzy Modeling with Spatial Information for Geographic Problems, provides many stimulating examples of advances in geographical research based on approaches using fuzzy sets and related technologies.
Reviews
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)
Editors and Affiliations
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Dept. of Electrical Engineering and Computer Science, Tulane University, New Orleans, USA
Frederick E. Petry
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Dept. of Geography, University of Toronto at Mississauga, Mississauga, Canada
Vincent B. Robinson
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Dept. of Computer Science and Statistics, University of Southern Mississippi, Hattiesburg, USA
Maria A. Cobb
