图书简介 馆藏图书馆

Chapter 1. Introduction; 1.1 Spatial data analysis; 1.2 Purpose of the book; 1.3 Key concepts; 1.4 Structure of the book; 1.5 Further reading; Chapter 2. Key concepts 1: GIS; 2.1 Introduction; 2.1 Data and data models; 2.2.1 Raster data; 2.2.2 Vector data; 2.2.3 Topology; 2.2.4 Rasters and vectors in GIS software; 2.3 Databases; 2.3.1 Database management; 2.3.2 The Geodatabase; 2.5 Georeferencing; 2.6 Geocoding; 2.7 Spatial scale; 2.8 Spatial data collection; 2.9 Sources of data error; 2.9.1 Uncertainty in spatial data analysis; 2.10 Visualising spatial data; 2.11.1 Boolean logic; Chapter 3. Key concepts 2: statistics; 3.1 Introduction; 3.2 Univariate statistics; 3.3 Multivariate statistics; 3.4 Inferential statistics; 3.5 Statistics and spatial data; 3.6 Summary; 3.7 Further reading; Chapter 4. Key concepts 3: spatial data analysis; 4.1 Introduction; 4.2 Distances; 4.3 Measuring lengths and perimeters; 4.3.1 Length of vector features; 4.4 Measuring areas; 4.4.1 Areas of polygons; 4.5 Distances from objects: buffers; 4.5.1 Vector buffers; 4.5.2 Raster proximity; 4.6 Moving windows: basic statistics in sub-regions; 4.7 Geographical weights; 4.9 The ecological fallacy and the modifiable areal unit problem; 4.10 Merging polygons; 4.11 Summary; 4.12 Further reading; Chapter 5. Combining data layers; 5.1 Introduction; 5.2 Multiple features: overlays; 5.2.1 Point in polygon; 5.2.2 Overlay operators; 5.2.3 ’Cookie cutter’ operations: erase and clip; 5.2.4 Applications and problems; 5.3 Multicriteria decision analysis; 5.4 Case study; 5.5 Summary; 5.6 Further reading; Chapter 6. Network analysis; 6.1 Introduction; 6.2 Networks; 6.3 Network connectivity; 6.4 Summaries of network characteristics; 6.5 Identifying shortest paths; 6.6 The travelling salesperson problem; 6.7 Location-allocation problems; 6.8 Case study; 6.9 Summary; 6.10 Further reading; Chapter 7. Exploring spatial point patterns; 7.1 Introduction; 7.2 Basic measures; 7.3 Exploring spatial variations in point intensity; 7.3.1 Quadrats; 7.3.2 Kernel estimation; 7.4 measures based on distances between events; 7.4.1 Nearest neighbour methods; 7.4.2 K function; 7.5 Applications and other issues; 7.6 Case study; 7.7 Summary; 7.8 Further reading; Chapter 8. Exploring spatial patterning in data values; 8.1 Introduction; 8.2 Spatial autocorrelation; 8.3 Local statistics; 8.4 Local univariate measures; 8.4.1 Local spatial autocorrelation; 8.5 Regression and correlation; 8.5.1 Spatial regression; 8.5.2 Moving window regression (MWR); 8.5.3 Geographically weighted regression (GWR); 8.6 Other approaches; 8.7 Case studies; 8.7.1 Spatial autocorrelation analysis; 8.7.2 GWR; 8.8 Summary; 8.9 Further reading; Chapter 9. Spatial interpolation; 9.1 Introduction; 9.2 Interpolation; 9.3 Triangulated irregular networks; 9.4 Regression for prediction; 9.5 Inverse distance weighting; 9.6 Thin plate splines; 9.7 Ordinary kriging; 9.7.1 Variogram; 9.7.2 Kriging; 9.8 Other approaches and other issues; 9.9 Areal interpolation; 9.10 Case studies; 9.10.1 Variogram estimation; 9.10.2 Spatial interpolation; 9.11 Summary; 9.12 Further reading; Chapter 10. Analysis of grids and surfaces; 10.1 Introduction; 10.2 Map algebra; 10.3 Image processing; 10.4 Spatial filters; 10.5 Derivatives of altitude; 10.6 Other products derived from surfaces; 10.7 Case study; 10.8 Summary; 10.9 Further reading; Chapter 11. Summary; 11.1 Review of key concepts; 11.2 Other issues; 11.3 Problems; 11.4 Where next?; 11.5 Summary and conclusions; References; Appendix A. Matrix multiplication; Appendix B. The exponential function; Appendix C. The inverse tangent Appendix D. Line Intersection Appendix E. Ordinary least squares Appendix F. Ordinary kriging system Appendix G. Problems and solutions

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