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008 150130s2010 njumb b a001 0 eng d
010 _a2009042594
020 _a9780470288573
_qcloth
020 _a0470288574
_qcloth
040 _aDLC
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_dYDX
_dBTCTA
_dUKM
_dYDXCP
_dCDX
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_beng
_erda
049 _aBAUN_MERKEZ
050 0 0 _aG70.212
_b.O88 2010
082 0 0 _222
100 1 _aO'Sullivan, David,
_d1966-
245 1 0 _aGeographic information analysis /
_cDavid O'Sullivan and David J. Unwin.
250 _a2nd edition.
264 1 _aHoboken, N.J. :
_bJohn Wiley & Sons,
_cc2010.
300 _axix, 405 pages :
_billustrations maps ;
_c25 cm.
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
504 _aIncludes bibliographical references and index.
505 0 0 _t-- =505 00
_t-- Contents
_t Preface to the Second Edition
_t Acknowledgments
_t Preface to the First Edition
_t 1 Geographic Information Analysis and Spatial Data
_t Chapter Objectives
_t 1.1 Introduction
_t 1.2 Spatial Data Types
_t 1.3 Some Complications
_t 1.4 Scales for Attribute Description
_t 1.5 GIS and Spatial Data Manipulation
_t 1.6 The Road Ahead
_t Chapter Review
_t References
_t 2 The Pitfalls and Potential of Spatial Data
_t Chapter Objectives
_t 2.1 Introduction
_t 2.2 The Bad News: The Pitfalls of Spatial Data
_t 2.3 The Good News: The Potential of Spatial Data
_t Chapter Review
_t References
_t 3 Fundamentals-Mapping It Out
_t Chapter Objectives
_t 3.1 Introduction: The Cartographic Tradition
_t 3.2 Geovisualization and Analysis
_t 3.3 The Graphic Variables of Jacques Bertin
_t 3.4 New Graphic Variables
_t 3.5 Issues in Geovisualization
_t 3.6 Mapping and Exploring Points
_t 3.7 Mapping and Exploring Areas
_t 3.8 Mapping and Exploring Fields
_t 3.9 The Spatialization of Nonspatial Data
_t 3.10 Conclusion
_t Chapter Review
_t References
_t 4 Fundamentals-Maps as Outcomes of Processes
_t Chapter Objectives
_t 4.1 Introduction: Maps and Processes
_t 4.2 Processes and the Patterns They Make
_t 4.3 Predicting the Pattern Generated by a Process
_t 4.4 More Definitions
_t 4.5 Stochastic Processes in Lines, Areas, and Fields
_t 4.6 Conclusions
_t Chapter Review
_t References
_t 5 Point Pattern Analysis
_t Chapter Objectives
_t 5.1 Introduction
_t 5.2 Describing a Point Pattern
_t 5.3 Assessing Point Patterns Statistically
_t 5.4 Monte Carlo Testing
_t 5.5 Conclusions
_t Chapter Review
_t References
_t 6 Practical Point Pattern Analysis
_t Chapter Objectives
_t 6.1 Introduction: Problems of Spatial Statistical Analysis
_t 6.2 Alternatives to Classical Statistical Inference
_t 6.3 Alternatives to IRP/CSR
_t 6.4 Point Pattern Analysis in the Real World
_t 6.5 Dealing with Inhomogeneity
_t 6.6 Focused Approaches
_t 6.7 Cluster Detection: Scan Statistics
_t 6.8 Using Density and Distance: Proximity Polygons
_t 6.9 A Note on Distance Matrices and Point Pattern Analysis
_t Chapter Review
_t References
_t 7 Area Objects and Spatial Autocorrelation
_t Chapter Objectives
_t 7.1 Introduction: Area Objects Revisited
_t 7.2 Types of Area Objects
_t 7.3 Geometric Properties of Areas
_t 7.4 Measuring Spatial Autocorrelation
_t 7.5 An Example: Tuberculosis in Auckland, 2001-2006
_t 7.6 Other Approaches
_t Chapter Review
_t References
_t 8 Local Statistics
_t Chapter Objectives
_t 8.1 Introduction: Think Geographically, Measure Locally
_t 8.2 Defining the Local: Spatial Structure (Again)
_t 8.3 An Example: The Getis-Ord Gi and Gi Statistics
_t 8.4 Inference with Local Statistics
_t 8.5 Other Local Statistics
_t 8.6 Conclusions: Seeing the World Locally
_t Chapter Review
_t References
_t 9 Describing and Analyzing Fields
_t Chapter Objectives
_t 9.1 Introduction: Scalar and Vector Fields Revisited
_t 9.2 Modeling and Storing Field Data
_t 9.3 Spatial Interpolation
_t 9.4 Derived Measures on Surfaces
_t 9.5 Map Algebra
_t 9.6 Conclusions
_t Chapter Review
_t References
_t 10 Knowing the Unknowable: The Statistics of Fields
_t Chapter Objectives
_t 10.1 Introduction
_t 10.2 Regression on Spatial Coordinates: Trend Surface Analysis
_t 10.3 The Square Root Differences Cloud and the (Semi-) Variogram
_t 10.4 A Statistical Approach to Interpolation: Kriging
_t 10.5 Conclusions
_t Chapter Review
_t References
_t 11 Putting Maps Together—Map Overlay
_t Chapter Objectives
_t 11.1 Introduction
_t 11.2 Boolean Map Overlay and Sieve Mapping
_t 11.3 A General Model for Alternatives to Boolean Overlay
_t 11.4 Indexed Overlay and Weighted Linear Combination
_t 11.5 Weights of Evidence
_t 11.6 Model-Driven Overlay Using Regression
_t 11.7 Conclusions
_t Chapter Review
_t References
_t 12 New Approaches to Spatial Analysis
_t Chapter Objectives
_t 12.1 The Changing Technological Environment
_t 12.2 The Changing Scientific Environment
_t 12.3 Geocomputation
_t 12.4 Spatial Models
_t 12.5 The Grid and the Cloud: Supercomputing for Dummies
_t 12.6 Conclusions: Neogeographic Information Analysis?
_t Chapter Review
_t References
_t Appendix A: Notation, Matrices, and Matrix Mathematics
_t A.1 Introduction
_t A.2 Some Preliminary Notes on Notation
_t A.3 Matrix Basics and Notation
_t A.4 Simple Matrix Mathematics
_t A.5 Solving Simultaneous Equations Using Matrices
_t A.6 Matrices, Vectors, and Geometry
_t A.7 Eigenvectors and Eigenvalues
_t Reference
650 0 _aGeographic information systems.
650 0 _aSpatial analysis (Statistics)
700 1 _aUnwin, D.
_q(David John)
942 _2lcc
_cKT
999 _c33553
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