{"product_id":"geographic-information-analysis-isbn-9780470288573","title":"Geographic Information Analysis","description":"\u003cb\u003eClear, up-to-date coverage of methods for analyzing geographical information in a GIS context\u003c\/b\u003e \u003cp\u003e\u003ci\u003eGeographic Information Analysis, Second Edition\u003c\/i\u003e is fully updated to keep pace with the most recent developments of spatial analysis in a geographic information systems (GIS) environment. Still focusing on the universal aspects of this science, this revised edition includes new coverage on geovisualization and mapping as well as recent developments using local statistics.\u003c\/p\u003e \u003cp\u003eBuilding on the fundamentals, this book explores such key concepts as spatial processes, point patterns, and autocorrelation in area data, as well as in continuous fields. Also addressed are methods for combining maps and performing computationally intensive analysis. New chapters tackle mapping, geovisualization, and local statistics, including the Moran Scatterplot and Geographically Weighted Regression (GWR). An appendix provides a primer on linear algebra using matrices.\u003c\/p\u003e \u003cp\u003eComplete with chapter objectives, summaries, \"thought exercises,\" explanatory diagrams, and a chapter-by-chapter bibliography, \u003ci\u003eGeographic Information Analysis\u003c\/i\u003e is a practical book for students, as well as a valuable resource for researchers and professionals in the industry.\u003c\/p\u003e  Preface to the Second Edition.  \u003cp\u003eAcknowledgments.\u003c\/p\u003e \u003cp\u003ePreface to the First Edition.\u003c\/p\u003e \u003cp\u003e1 Geographic Information Analysis and Spatial Data.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e1.1 Introduction.\u003c\/p\u003e \u003cp\u003e1.2 Spatial Data Types.\u003c\/p\u003e \u003cp\u003e1.3 Some Complications.\u003c\/p\u003e \u003cp\u003e1.4 Scales for Attribute Description.\u003c\/p\u003e \u003cp\u003e1.5 GIS and Spatial Data Manipulation.\u003c\/p\u003e \u003cp\u003e1.6 The Road Ahead.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e2 The Pitfalls and Potential of Spatial Data.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e2.1 Introduction.\u003c\/p\u003e \u003cp\u003e2.2 The Bad News: The Pitfalls of Spatial Data.\u003c\/p\u003e \u003cp\u003e2.3 The Good News: The Potential of Spatial Data.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e3 Fundamentals-Mapping It Out.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e3.1 Introduction: The Cartographic Tradition.\u003c\/p\u003e \u003cp\u003e3.2 Geovisualization and Analysis.\u003c\/p\u003e \u003cp\u003e3.3 The Graphic Variables of Jacques Bertin.\u003c\/p\u003e \u003cp\u003e3.4 New Graphic Variables.\u003c\/p\u003e \u003cp\u003e3.5 Issues in Geovisualization.\u003c\/p\u003e \u003cp\u003e3.6 Mapping and Exploring Points.\u003c\/p\u003e \u003cp\u003e3.7 Mapping and Exploring Areas.\u003c\/p\u003e \u003cp\u003e3.8 Mapping and Exploring Fields.\u003c\/p\u003e \u003cp\u003e3.9 The Spatialization of Nonspatial Data.\u003c\/p\u003e \u003cp\u003e3.10 Conclusion.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e4 Fundamentals-Maps as Outcomes of Processes.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e4.1 Introduction: Maps and Processes.\u003c\/p\u003e \u003cp\u003e4.2 Processes and the Patterns They Make.\u003c\/p\u003e \u003cp\u003e4.3 Predicting the Pattern Generated by a Process.\u003c\/p\u003e \u003cp\u003e4.4 More Definitions.\u003c\/p\u003e \u003cp\u003e4.5 Stochastic Processes in Lines, Areas, and Fields.\u003c\/p\u003e \u003cp\u003e4.6 Conclusions.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e5 Point Pattern Analysis.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e5.1 Introduction.\u003c\/p\u003e \u003cp\u003e5.2 Describing a Point Pattern.\u003c\/p\u003e \u003cp\u003e5.3 Assessing Point Patterns Statistically.\u003c\/p\u003e \u003cp\u003e5.4 Monte Carlo Testing.\u003c\/p\u003e \u003cp\u003e5.5 Conclusions.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e6 Practical Point Pattern Analysis.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e6.1 Introduction: Problems of Spatial Statistical Analysis.\u003c\/p\u003e \u003cp\u003e6.2 Alternatives to Classical Statistical Inference.\u003c\/p\u003e \u003cp\u003e6.3 Alternatives to IRP\/CSR.\u003c\/p\u003e \u003cp\u003e6.4 Point Pattern Analysis in the Real World.\u003c\/p\u003e \u003cp\u003e6.5 Dealing with Inhomogeneity.\u003c\/p\u003e \u003cp\u003e6.6 Focused Approaches.\u003c\/p\u003e \u003cp\u003e6.7 Cluster Detection: Scan Statistics.\u003c\/p\u003e \u003cp\u003e6.8 Using Density and Distance: Proximity Polygons.\u003c\/p\u003e \u003cp\u003e6.9 A Note on Distance Matrices and Point Pattern Analysis.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e7 Area Objects and Spatial Autocorrelation.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e7.1 Introduction: Area Objects Revisited.\u003c\/p\u003e \u003cp\u003e7.2 Types of Area Objects.\u003c\/p\u003e \u003cp\u003e7.3 Geometric Properties of Areas.\u003c\/p\u003e \u003cp\u003e7.4 Measuring Spatial Autocorrelation.\u003c\/p\u003e \u003cp\u003e7.5 An Example: Tuberculosis in Auckland, 2001-2006.\u003c\/p\u003e \u003cp\u003e7.6 Other Approaches.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e8 Local Statistics.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e8.1 Introduction: Think Geographically, Measure Locally.\u003c\/p\u003e \u003cp\u003e8.2 Defining the Local: Spatial Structure (Again).\u003c\/p\u003e \u003cp\u003e8.3 An Example: The Getis-Ord G\u003csub\u003ei\u003c\/sub\u003e and G\u003csub\u003ei\u003c\/sub\u003e Statistics.\u003c\/p\u003e \u003cp\u003e8.4 Inference with Local Statistics.\u003c\/p\u003e \u003cp\u003e8.5 Other Local Statistics.\u003c\/p\u003e \u003cp\u003e8.6 Conclusions: Seeing the World Locally.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e9 Describing and Analyzing Fields.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e9.1 Introduction: Scalar and Vector Fields Revisited.\u003c\/p\u003e \u003cp\u003e9.2 Modeling and Storing Field Data.\u003c\/p\u003e \u003cp\u003e9.3 Spatial Interpolation.\u003c\/p\u003e \u003cp\u003e9.4 Derived Measures on Surfaces.\u003c\/p\u003e \u003cp\u003e9.5 Map Algebra.\u003c\/p\u003e \u003cp\u003e9.6 Conclusions.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e10 Knowing the Unknowable: The Statistics of Fields.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e10.1 Introduction.\u003c\/p\u003e \u003cp\u003e10.2 Regression on Spatial Coordinates: Trend Surface Analysis.\u003c\/p\u003e \u003cp\u003e10.3 The Square Root Differences Cloud and the (Semi-) Variogram.\u003c\/p\u003e \u003cp\u003e10.4 A Statistical Approach to Interpolation: Kriging.\u003c\/p\u003e \u003cp\u003e10.5 Conclusions.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e11 Putting Maps Together—Map Overlay.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e11.1 Introduction.\u003c\/p\u003e \u003cp\u003e11.2 Boolean Map Overlay and Sieve Mapping.\u003c\/p\u003e \u003cp\u003e11.3 A General Model for Alternatives to Boolean Overlay.\u003c\/p\u003e \u003cp\u003e11.4 Indexed Overlay and Weighted Linear Combination.\u003c\/p\u003e \u003cp\u003e11.5 Weights of Evidence.\u003c\/p\u003e \u003cp\u003e11.6 Model-Driven Overlay Using Regression.\u003c\/p\u003e \u003cp\u003e11.7 Conclusions.\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e12 New Approaches to Spatial Analysis.\u003c\/p\u003e \u003cp\u003eChapter Objectives.\u003c\/p\u003e \u003cp\u003e12.1 The Changing Technological Environment.\u003c\/p\u003e \u003cp\u003e12.2 The Changing Scientific Environment.\u003c\/p\u003e \u003cp\u003e12.3 Geocomputation.\u003c\/p\u003e \u003cp\u003e12.4 Spatial Models.\u003c\/p\u003e \u003cp\u003e12.5 The Grid and the Cloud: Supercomputing for Dummies.\u003c\/p\u003e \u003cp\u003e12.6 Conclusions: Neogeographic Information Analysis?\u003c\/p\u003e \u003cp\u003eChapter Review.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eAppendix A: Notation, Matrices, and Matrix Mathematics.\u003c\/p\u003e \u003cp\u003eA.1 Introduction.\u003c\/p\u003e \u003cp\u003eA.2 Some Preliminary Notes on Notation.\u003c\/p\u003e \u003cp\u003eA.3 Matrix Basics and Notation.\u003c\/p\u003e \u003cp\u003eA.4 Simple Matrix Mathematics.\u003c\/p\u003e \u003cp\u003eA.5 Solving Simultaneous Equations Using Matrices.\u003c\/p\u003e \u003cp\u003eA.6 Matrices, Vectors, and Geometry.\u003c\/p\u003e \u003cp\u003eA.7 Eigenvectors and Eigenvalues.\u003c\/p\u003e \u003cp\u003eReference.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e \u003cp\u003e“http:\/\/www.amazon.com\/exec\/obidos\/ASIN\/0470288574\/esristore-20\"\u003cbr\u003eThis text provides a well organized introduction to the fundamental concepts of spatial analysis for GIS students.” (\u003ci\u003eGISWeekly\u003c\/i\u003e, 13 December 2012)\u003c\/p\u003e  \u003cb\u003eDavid O'Sullivan, PhD\u003c\/b\u003e, is Associate Professor of Geography at the University of Auckland, New Zealand.  \u003cp\u003e\u003cb\u003eDavid J. Unwin, MPhil\u003c\/b\u003e, formerly professor of geography at Birkbeck College in the University of London, UK, is now retired. He is also the co-author of \u003ci\u003eComputer Programming for Geographers\u003c\/i\u003e (with J.A. Dawson) and coeditor of \u003ci\u003eVisualization in Geographic Information Systems\u003c\/i\u003e (with Hilary M. Hearnshaw), both published by Wiley.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989281095909,"sku":"NP9780470288573","price":135.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780470288573.jpg?v=1761783502","url":"https:\/\/k12savings.com\/products\/geographic-information-analysis-isbn-9780470288573","provider":"K12savings","version":"1.0","type":"link"}