432 pages, 88 figs, 33 tabs
Provides a wide-ranging treatment of the field of spatial data analysis. The book begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and policy related research. Covers fundamental problems concerning how attributes in geographical space are represented, to the latest methods of exploratory spatial data analysis and spatial modelling.
Preface; Readership; Acknowledgements; Introduction; Part I. The Context for Spatial Data Analysis: 1. Spatial data analysis: scientific and policy context; 2. The nature of spatial data; Part II. Spatial Data: Obtaining Data And Quality Issues: 3. Obtaining spatial data through sampling; 4. Data quality: implications for spatial data analysis; Part III. The Exploratory Analysis of Spatial Data: 5. Exploratory analysis of spatial data; 6. Exploratory spatial data analysis: visualisation methods; 7. Exploratory spatial data analysis: numerical methods; Part IV. Hypothesis Testing in the Presence of Spatial Autocorrelation: 8. Hypothesis testing in the presence of spatial dependence; Part V. Modeling Spatial Data: 9. Models for the statistical analysis of spatial data; 10. Statistical modeling of spatial variation: descriptive modeling; 11. Statistical modeling of spatial variation: explanatory modeling; Appendices; References; Index.
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Robert Haining is Professor of Human Geography at the University of Cambridge.