Geographic information analysis / David O'Sullivan and David J. Unwin.

Includes bibliographical references and index.

-- =505 00 -- Contents Preface to the Second Edition Acknowledgments Preface to the First Edition 1 Geographic Information Analysis and Spatial Data Chapter Objectives 1.1 Introduction 1.2 Spatial Data Types 1.3 Some Complications 1.4 Scales for Attribute Description 1.5 GIS and Spatial Data Manipulation 1.6 The Road Ahead Chapter Review References 2 The Pitfalls and Potential of Spatial Data Chapter Objectives 2.1 Introduction 2.2 The Bad News: The Pitfalls of Spatial Data 2.3 The Good News: The Potential of Spatial Data Chapter Review References 3 Fundamentals-Mapping It Out Chapter Objectives 3.1 Introduction: The Cartographic Tradition 3.2 Geovisualization and Analysis 3.3 The Graphic Variables of Jacques Bertin 3.4 New Graphic Variables 3.5 Issues in Geovisualization 3.6 Mapping and Exploring Points 3.7 Mapping and Exploring Areas 3.8 Mapping and Exploring Fields 3.9 The Spatialization of Nonspatial Data 3.10 Conclusion Chapter Review References 4 Fundamentals-Maps as Outcomes of Processes Chapter Objectives 4.1 Introduction: Maps and Processes 4.2 Processes and the Patterns They Make 4.3 Predicting the Pattern Generated by a Process 4.4 More Definitions 4.5 Stochastic Processes in Lines, Areas, and Fields 4.6 Conclusions Chapter Review References 5 Point Pattern Analysis Chapter Objectives 5.1 Introduction 5.2 Describing a Point Pattern 5.3 Assessing Point Patterns Statistically 5.4 Monte Carlo Testing 5.5 Conclusions Chapter Review References 6 Practical Point Pattern Analysis Chapter Objectives 6.1 Introduction: Problems of Spatial Statistical Analysis 6.2 Alternatives to Classical Statistical Inference 6.3 Alternatives to IRP/CSR 6.4 Point Pattern Analysis in the Real World 6.5 Dealing with Inhomogeneity 6.6 Focused Approaches 6.7 Cluster Detection: Scan Statistics 6.8 Using Density and Distance: Proximity Polygons 6.9 A Note on Distance Matrices and Point Pattern Analysis Chapter Review References 7 Area Objects and Spatial Autocorrelation Chapter Objectives 7.1 Introduction: Area Objects Revisited 7.2 Types of Area Objects 7.3 Geometric Properties of Areas 7.4 Measuring Spatial Autocorrelation 7.5 An Example: Tuberculosis in Auckland, 2001-2006 7.6 Other Approaches Chapter Review References 8 Local Statistics Chapter Objectives 8.1 Introduction: Think Geographically, Measure Locally 8.2 Defining the Local: Spatial Structure (Again) 8.3 An Example: The Getis-Ord Gi and Gi Statistics 8.4 Inference with Local Statistics 8.5 Other Local Statistics 8.6 Conclusions: Seeing the World Locally Chapter Review References 9 Describing and Analyzing Fields Chapter Objectives 9.1 Introduction: Scalar and Vector Fields Revisited 9.2 Modeling and Storing Field Data 9.3 Spatial Interpolation 9.4 Derived Measures on Surfaces 9.5 Map Algebra 9.6 Conclusions Chapter Review References 10 Knowing the Unknowable: The Statistics of Fields Chapter Objectives 10.1 Introduction 10.2 Regression on Spatial Coordinates: Trend Surface Analysis 10.3 The Square Root Differences Cloud and the (Semi-) Variogram 10.4 A Statistical Approach to Interpolation: Kriging 10.5 Conclusions Chapter Review References 11 Putting Maps Together—Map Overlay Chapter Objectives 11.1 Introduction 11.2 Boolean Map Overlay and Sieve Mapping 11.3 A General Model for Alternatives to Boolean Overlay 11.4 Indexed Overlay and Weighted Linear Combination 11.5 Weights of Evidence 11.6 Model-Driven Overlay Using Regression 11.7 Conclusions Chapter Review References 12 New Approaches to Spatial Analysis Chapter Objectives 12.1 The Changing Technological Environment 12.2 The Changing Scientific Environment 12.3 Geocomputation 12.4 Spatial Models 12.5 The Grid and the Cloud: Supercomputing for Dummies 12.6 Conclusions: Neogeographic Information Analysis? Chapter Review References Appendix A: Notation, Matrices, and Matrix Mathematics A.1 Introduction A.2 Some Preliminary Notes on Notation A.3 Matrix Basics and Notation A.4 Simple Matrix Mathematics A.5 Solving Simultaneous Equations Using Matrices A.6 Matrices, Vectors, and Geometry A.7 Eigenvectors and Eigenvalues Reference