Geographic Information Analysis
暫譯: 地理資訊分析
David O'Sullivan, David Unwin
- 出版商: Wiley
- 出版日期: 2002-11-15
- 定價: $2,600
- 售價: 5.0 折 $1,300
- 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)
**描述**
地理資訊分析提供了在地理資訊系統環境中進行空間分析的基礎知識，並且涵蓋了最新的方法。這本書專注於空間數據及其分析的普遍性，探討了許多地理資訊系統中可用方法的科學假設和限制。
在整個討論中，地圖作為空間隨機過程的實現的基本概念是核心。書中涵蓋了關鍵的空間概念，包括點模式、線物件和網絡、區域物件以及連續場。針對每一種概念，書中都探討了分析技術，並介紹了結合地圖、探索多變量數據以及執行計算密集型分析的方法。附錄提供了有關基本統計和使用矩陣的線性代數的入門知識。
《地理資訊分析》完整地包含了章節目標、摘要、思考練習、豐富的解釋性圖表以及註釋書目，是一本實用的書籍，適合學生使用，同時也是研究人員和業界專業人士的寶貴資源。
**目錄**
前言
1. 地理資訊分析與空間數據
章節目標
1.1 介紹
1.2 空間數據類型
1.3 屬性描述的尺度
1.4 GIS分析、空間數據操作與空間分析
1.5 結論
章節回顧
參考文獻
2. 空間數據的陷阱與潛力
章節目標
2.1 介紹
2.2 壞消息：空間數據的陷阱
2.3 好消息：空間數據的潛力
2.4 預覽：變異數雲與半變異數
章節回顧
參考文獻
3. 基礎知識：地圖作為過程的結果
章節目標
3.1 介紹
3.2 過程及其產生的模式
3.3 預測過程生成的模式
3.4 更多定義
3.5 線、區域和場中的隨機過程
3.6 結論
章節回顧
參考文獻
4. 點模式分析
章節目標
4.1 介紹
4.2 描述點模式
4.3 基於密度的點模式測量
4.4 基於距離的點模式測量
4.5 統計評估點模式
4.6 空間統計分析的兩個批評
4.7 結論
章節回顧
參考文獻
5. 實用的點模式分析
章節目標
5.1 點模式分析與聚類檢測
5.2 基本點模式測量的擴展
5.3 使用密度和距離：鄰近多邊形
5.4 關於距離矩陣和點模式分析的說明
5.5 結論
章節回顧
參考文獻
6. 線與網絡
章節目標
6.1 介紹
6.2 表示和儲存線性實體
6.3 線長：不止於表面
6.4 線數據中的連接：樹和圖
6.5 地理線數據的統計分析
6.6 結論
章節回顧
參考文獻
7. 區域物件與空間自相關
章節目標
7.1 介紹
7.2 區域物件的類型
7.3 區域的幾何特性
7.4 空間自相關：引入聯接計數方法
7.5 完整範例：2000年美國總統選舉
7.6 其他空間自相關的測量
7.7 空間關聯的局部指標
章節回顧
參考文獻
8. 描述與分析場
章節目標
8.1 介紹
8.2 建模與儲存場數據
8.3 空間插值
8.4 表面的衍生測量
8.5 結論
章節回顧
參考文獻
9. 知道不可知的：場的統計
章節目標
9.1 介紹
9.2 回歸回顧
9.3 空間坐標上的回歸：趨勢面分析
9.4 插值的統計方法：克里金法
9.5 結論
章節回顧
參考文獻
10. 組合地圖：地圖重疊
章節目標
10.1 介紹
10.2 多邊形重疊與篩選映射
10.3 簡單布林多邊形重疊中的問題
10.4 朝向一般模型：布林重疊的替代方案
10.5 結論
章節回顧
參考文獻
11. 多變量數據、多維空間與空間化
章節目標
11.1 介紹
11.2 多變量數據與多維空間
11.3 距離、差異與相似性
11.4 聚類分析：識別相似觀察的群體
11.5 空間化：映射多變量數據
11.6 減少變量數量：主成分分析
11.7 結論
章節回顧
參考文獻
12. 空間分析的新方法
章節目標
12.1 介紹
12.2 地理計算
12.3 空間模型
12.4 結論
章節回顧
參考文獻
A. 統計學的基本要素
A.1 介紹
A.2 描述數據
A.3 機率理論
A.4 過程與隨機變數
A.5 抽樣分佈與假設檢定
A.6 範例
參考文獻
B. 矩陣與矩陣數學
B.1 介紹
B.2 矩陣基礎與符號
B.3 簡單數學
B.4 使用矩陣解聯立方程
B.5 矩陣、向量與幾何
參考文獻
索引
