Geographic Information Analysis
David O'Sullivan, David Unwin
- 出版商: Wiley
- 出版日期: 2002-11-15
- 定價: $2,600
- 售價: 1.5 折 $399
- 語言: 英文
- 頁數: 448
- 裝訂: Hardcover
- ISBN: 0471211761
- ISBN-13: 9780471211761
-
相關分類:
地理資訊系統 Gis
-
其他版本:
Geographic Information Analysis, 2/e (Hardcover)
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商品描述
Clear, up-to-date coverage of methods for analyzing geographical information in a GIS context
Geographic Information Analysis presents clear and up-to-date coverage of the foundations of spatial analysis in a geographic information systems environment. Focusing on the universal aspects of spatial data and their analysis, this book covers the scientific assumptions and limitations of methods available in many geographic information systems.
Throughout, the fundamental idea of a map as a realization of a spatial stochastic process is central to the discussion. Key spatial concepts are covered, including point pattern, line objects and networks, area objects, and continuous fields. Analytical techniques for each of these are addressed, as are methods for combining maps, exploring multivariate data, and performing computationally intensive analysis. Appendixes provide primers on basic statistics and linear algebra using matrices.
Complete with chapter objectives, summaries, "thought exercises," a wealth of explanatory diagrams, and an annotated bibliography, Geographic Information Analysis is a practical book for students, as well as a valuable resource for researchers and professionals in the industry.
Table of Contents
Preface.
1. Geographic Information Analysis and Spatial Data.
Chapter Objectives.
1.1 Introduction.
1.2 Spatial Data Types.
1.3 Scales for Attribute Description.
1.4 GIS Analysis, Spatial Data Manipulation, and Spatial Analysis.
1.5 Conclusion.
Chapter Review.
References.
2. The Pitfalls and Potential of Spatial Data.
Chapter Objectives.
2.1 Introduction.
2.2 The Bad News: The Pitfalls of Spatial Data.
2.3 The Good News: The Potential of Spatial Data.
2.4 Preview: The Variogram Cloud and the Semivariogram.
Chapter Review.
References.
3. Fundamentals: Maps as Outcomes of Processes.
Chapter Objectives.
3.1 Introduction.
3.2 Processes and the Patterns They Make.
3.3 Predicting the Pattern Generated by a Process.
3.4 More Definitions.
3.5 Stochastic Processes in Lines, Areas, and Fields.
3.6 Conclusion.
Chapter Review.
References.
4. Point Pattern Analysis.
Chapter Objectives.
4.1 Introduction.
4.2 Describing a Point Pattern.
4.3 Density-Based Point Pattern Measures.
4.4 Distance-Based Point Pattern Measures.
4.5 Assessing Point Patterns Statistically.
4.6 Two Critiques of Spatial Statistical Analysis.
4.7 Conclusion.
Chapter Review.
References.
5. Practical Point Pattern Analysis.
Chapter Objectives.
5.1 Point Pattern Analysis versus Cluster Detection.
5.2 Extensions of Basic Point Pattern Measures.
5.3 Using Density and Distance: Proximity Polygons.
5.4 Note on Distance Matrices and Point Pattern Analysis.
5.5 Conclusion.
Chapter Review.
References.
6. Lines and Networks.
Chapter Objectives.
6.1 Introduction.
6.2 Representing and Storing Linear Entities.
6.3 Line Length: More Than Meets the Eye.
6.4 Connection in Line Data: Trees and Graphs.
6.5 Statistical Analysis of Geographical Line Data.
6.6 Conclusion.
Chapter Review.
References.
7. Area Objects and Spatial Autocorrelation.
Chapter Objectives.
7.1 Introduction.
7.2 Types of Area Object.
7.3 Geometric Properties of Areas.
7.4 Spatial Autocorrelation: Introducing the Joins Count Approach.
7.5 Fully Worked Example: The 2000 U.S. Presidential Election.
7.6 Other Measures of Spatial Autocorrelation.
7.7 Local Indicators of Spatial Association.
Chapter Review.
References.
8. Describing and Analyzing Fields.
Chapter Objectives.
8.1 Introduction.
8.2 Modeling and Storing Field Data.
8.3 Spatial Interpolation.
8.4 Derived Measures on Surfaces.
8.5 Conclusion.
Chapter Review.
References.
9. Knowing the Unknowable: The Statistics of Fields.
Chapter Objectives.
9.1 Introduction.
9.2 Review of Regression.
9.3 Regression on Spatial Coordinates: Trend Surface Analysis.
9.4 Statistical Approach to Interpolation: Kriging.
9.5 Conclusion.
Chapter Review.
References.
10. Putting Maps Together: Map Overlay.
Chapter Objectives.
10.1 Introduction.
10.2 Polygon Overlay and Sieve Mapping.
10.3 Problems in Simple Boolean Polygon Overlay.
10.4 Toward a General Model: Alternatives to Boolean Overlay.
10.5 Conclusion.
Chapter Review.
References.
11. Multivariate Data, Multidimensional Space, and Spatialization.
Chapter Objectives.
11.1 Introduction.
11.2 Multivariate Data and Multidimensional Space.
11.3 Distance, Difference, and Similarity.
11.4 Cluster Analysis: Identifying Groups of Similar Observations.
11.5 Spatialization: Mapping Multivariate Data.
11.6 Reducing the Number of Variables: Principal Components Analysis.
11.7 Conclusion.
Chapter Review.
References.
12. New Approaches to Spatial Analysis.
Chapter Objectives.
12.1 Introduction.
12.2 Geocomputation.
12.3 Spatial Models.
12.4 Conclusion.
Chapter Review.
References.
A. The Elements of Statistics.
A.1 Introduction.
A.2 Describing Data.
A.3 Probability Theory.
A.4 Processes and Random Variables.
A.5 Sampling Distributions and Hypothesis Testing.
A.6 Example.
Reference.
B. Matrices and Matrix Mathematics.
B.1 Introduction.
B.2 Matrix Basics and Notation.
B.3 Simple Mathematics.
B.4 Solving Simultaneous Equations Using Matrices.
B.5 Matrices, Vectors, and Geometry.
Reference.
Index.
商品描述(中文翻譯)
《地理信息分析》是一本清晰且最新的地理信息系统环境下空间分析基础的覆盖范围广泛的书籍。本书关注空间数据及其分析的普遍方面，涵盖了许多地理信息系统中可用方法的科学假设和限制。
全书围绕地图作为空间随机过程的实现的基本概念展开讨论。重点介绍了点模式、线对象和网络、区域对象以及连续场等关键空间概念。针对每个概念，都介绍了相应的分析技术，以及合并地图、探索多变量数据和进行计算密集型分析的方法。附录提供了基本统计学和线性代数的入门知识。
《地理信息分析》具有章节目标、总结、思考练习、大量解释性图表和注释参考书目，是学生的实用教材，也是研究人员和行业专业人士的宝贵资源。
目录包括前言、第一章地理信息分析与空间数据、第二章空间数据的问题与潜力、第三章基础知识：地图作为过程的结果、第四章点模式分析、第五章实用点模式分析、第六章线和网络等内容。
