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SPATIAL DATA ANALYSIS: AN INTRODUCTION FOR GIS USERS 5E 2009 (P)
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ISBN: 9780199554324
類別: 地球科學/天文學Earth Science / Astronomy
出版社: OXFORD UNIVERSITY PRESS
作者: LLOYD
年份: 2009
裝訂別: 平裝
頁數: 218
定價: 860
售價: 774
原幣價: GBP 27.99
狀態: 缺書
。A focused introduction to the key ideas and methods from which readers can build a firm foundation in spatial data analysis.
。Assumes only limited prior knowledge of GIS and starts from first principles, making it ideal for anyone new to the field.
。Worked examples and case studies demonstrate all of the key methods introduced, to put principles into an applied context.
。The Online Resource Centre features the synthetic data and worked examples needed to enable readers to experiment with the methods detailed.

What is the shortest route between one point and another in a road network? Where is the incidence of disease the highest? How does rainfall correlate with altitude? How does the concentration of a pollutant vary in space, and where do high concentrations correlate with densely populated areas?

Geographical or spatial data play a vital role in many parts of daily life. We are dependent on information about where things are located and about the attributes of those things, either directly, as in the use of a map for navigating around a city, or indirectly, where we use resources like water or gas.

Making use of spatial data requires a whole set of approaches to extract information from those data and make them useful. Underpinning these approaches is the analysis of data.

Spatial Data Analysis introduces key principles about spatial data and provides guidance on methods for their exploration; it provides a set of key ideas or frameworks that will give the reader knowledge of the kinds of problems that can be tackled using the tools that are widely available for the analysis of spatial data.

The approach is gradual and systematic; the initial focus is on themes that follow through the rest of the book. These key ideas are introduced, illustrated, and restated to ensure that readers develop a clear understanding of them.

Beyond careful explanations, a clear understanding is fostered still further by numerous worked examples and case studies. In short, the stress is on first principles and reinforcement of key ideas throughout - on education rather than simply training, based on the conviction that users of spatial data analysis tools should know something about how the approaches work rather than simply how to apply them.

Table Of Contents

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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