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Geographic Information Analysis

ISBN-10: 0471211761
ISBN-13: 9780471211761
Edition: 2003
List price: $110.00
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Description: Geographic Information Analyses presents the spatial analytical foundation of geographic information systems which are instrumental to the emergent study of GIScience. This book covers spatial concepts such as points, lines, areas and surfaces, and  More...

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Book details

List price: $110.00
Copyright year: 2003
Publisher: John Wiley & Sons, Incorporated
Publication date: 11/15/2002
Binding: Hardcover
Pages: 448
Size: 6.25" wide x 9.25" long x 1.00" tall
Weight: 1.628
Language: English

Geographic Information Analyses presents the spatial analytical foundation of geographic information systems which are instrumental to the emergent study of GIScience. This book covers spatial concepts such as points, lines, areas and surfaces, and analytical techniques such as projection, nearest neighbor, fractals, triangulation, and geostatistics.

Preface
Geographic Information Analysis and Spatial Data
Chapter Objectives
Introduction
Spatial Data Types
Scales for Attribute Description
GIS Analysis, Spatial Data Manipulation, and Spatial Analysis
Conclusion
Chapter Review
References
The Pitfalls and Potential of Spatial Data
Chapter Objectives
Introduction
The Bad News: The Pitfalls of Spatial Data
The Good News: The Potential of Spatial Data
Preview: The Variogram Cloud and the Semivariogram
Chapter Review
References
Fundamentals: Maps as Outcomes of Processes
Chapter Objectives
Introduction
Processes and the Patterns They Make
Predicting the Pattern Generated by a Process
More Definitions
Stochastic Processes in Lines, Areas, and Fields
Conclusion
Chapter Review
References
Point Pattern Analysis
Chapter Objectives
Introduction
Describing a Point Pattern
Density-Based Point Pattern Measures
Distance-Based Point Pattern Measures
Assessing Point Patterns Statistically
Two Critiques of Spatial Statistical Analysis
Conclusion
Chapter Review
References
Practical Point Pattern Analysis
Chapter Objectives
Point Pattern Analysis versus Cluster Detection
Extensions of Basic Point Pattern Measures
Using Density and Distance: Proximity Polygons
Note on Distance Matrices and Point Pattern Analysis
Conclusion
Chapter Review
References
Lines and Networks
Chapter Objectives
Introduction
Representing and Storing Linear Entities
Line Length: More Than Meets the Eye
Connection in Line Data: Trees and Graphs
Statistical Analysis of Geographical Line Data
Conclusion
Chapter Review
References
Area Objects and Spatial Autocorrelation
Chapter Objectives
Introduction
Types of Area Object
Geometric Properties of Areas
Spatial Autocorrelation: Introducing the Joins Count Approach
Fully Worked Example: The 2000 U.S. Presidential Election
Other Measures of Spatial Autocorrelation
Local Indicators of Spatial Association
Chapter Review
References
Describing and Analyzing Fields
Chapter Objectives
Introduction
Modeling and Storing Field Data
Spatial Interpolation
Derived Measures on Surfaces
Conclusion
Chapter Review
References
Knowing the Unknowable: The Statistics of Fields
Chapter Objectives
Introduction
Review of Regression
Regression on Spatial Coordinates: Trend Surface Analysis
Statistical Approach to Interpolation: Kriging
Conclusion
Chapter Review
References
Putting Maps Together: Map Overlay
Chapter Objectives
Introduction
Polygon Overlay and Sieve Mapping
Problems in Simple Boolean Polygon Overlay
Toward a General Model: Alternatives to Boolean Overlay
Conclusion
Chapter Review
References
Multivariate Data, Multidimensional Space, and Spatialization
Chapter Objectives
Introduction
Multivariate Data and Multidimensional Space
Distance, Difference, and Similarity
Cluster Analysis: Identifying Groups of Similar Observations
Spatialization: Mapping Multivariate Data
Reducing the Number of Variables: Principal Components Analysis
Conclusion
Chapter Review
References
New Approaches to Spatial Analysis
Chapter Objectives
Introduction
Geocomputation
Spatial Models
Conclusion
Chapter Review
References
The Elements of Statistics
Introduction
Describing Data
Probability Theory
Processes and Random Variables
Sampling Distributions and Hypothesis Testing
Example
Reference
Matrices and Matrix Mathematics
Introduction
Matrix Basics and Notation
Simple Mathematics
Solving Simultaneous Equations Using Matrices
Matrices, Vectors, and Geometry
Reference
Index

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