Quantitative Methods and Socio-Economic Applications in GIS

333 Pages·2014·17.73 MB·English

by  Fahui Wang

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methods. … provides useful discussion of important methodological issues such as
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spatial autocorrelation and the modifiable areal unit problem. … an excellent book for d
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students and social scientists interested in various social and economic phenomena

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“… an excellent book with clear, meaningful, and well-designed examples. It’s one of
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the most useful books on my shelf!” i
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—Sara McLafferty, University of Illinois at Urbana-Champaign -
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See What’s New in the Second Edition: o
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• All project instructions are in ArcGIS 10.2 using geodatabase datasets o
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• New chapters on regionalization methods and Monte Carlo simulation i
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• Popular tasks automated as a convenient toolkit: Huff Model, 2SFCA accessibility A
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measure, regionalization, Garin–Lowry model, and Monte Carlo–based spatial
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• Advanced tasks now implemented in user-friendly programs or ArcGIS: centrality a
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indices, wasteful commuting measure, p-median problem, and traffic simulation io
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The second edition of a bestseller, Quantitative Methods and Socio-Economic s

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Applications in GIS (previously titled Quantitative Methods and Applications in GIS) n

details applications of quantitative methods in social science, planning, and public G
policy with a focus on spatial perspectives. The book integrates GIS and quantitative
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(computational) methods and demonstrates them in various policy-relevant socio- S
economic applications with step-by-step instructions and datasets. The book
demonstrates the diversity of issues where GIS can be used to enhance the studies
Second
related to socio-economic issues and public policy. Edition
K19056
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Second Edition
Quantitative Methods
and Socio-Economic
Applications in
GIS

Second Edition
Quantitative Methods
and Socio-Economic
Applications in
GIS
Fahui Wang
Boca Raton London New York
CRC Press is an imprint of the
Taylor & Francis Group, an informa business
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In loving memory of Katherine Z. Wang
To Lei and our three J’s (Jenny, Joshua, and Jacqueline)

Contents
List of Figures ..........................................................................................................xv
List of Tables ...........................................................................................................xix
Foreword .................................................................................................................xxi
Preface..................................................................................................................xxiii
Author ..................................................................................................................xxvii
List of Major GIS Datasets and Program Files .....................................................xxix
List of Quick References for Spatial Analysis Tasks ............................................xxxi
Section i GiS and Basic Spatial Analysis tasks
Chapter 1 Getting Started with ArcGIS: Data Management and
Basic Spatial Analysis Tools ................................................................3
1.1 Spatial and Attribute Data Management in ArcGIS .................3
1.1.1 Map Projections and Spatial Data Models ...................4
1.1.2 Attribute Data Management and Attribute Join ...........5
1.2 Spatial Analysis Tools in ArcGIS: Queries, Spatial Joins,
and Map Overlays ......................................................................7
1.3 Case Study 1: Mapping and Analyzing Population
Density Pattern in Baton Rouge, Louisiana ............................10
1.3.1 Part 1: Mapping the Population Density Pattern
across Census Tracts ..................................................10
1.3.2 Part 2: Analyzing the Population Density Pattern
across Concentric Rings .............................................16
1.4 Summary .................................................................................23
Appendix 1: Identifying Contiguous Polygons by Spatial
Analysis Tools .........................................................................23
Chapter 2 Measuring Distance and Time ...........................................................27
2.1 Measures of Distance ..............................................................27
2.2 Computing Network Distance and Time .................................29
2.3 Distance Decay Rule ...............................................................32
2.4 Case Study 2: Computing Distances and Travel Time to
Public Hospitals in Louisiana ..................................................33
2.4.1 Part 1: Measuring Euclidean and Manhattan
Distances ....................................................................34
2.4.2 Part 2: Measuring Travel Time ..................................38
2.5 Summary .................................................................................41
vii
viii Contents
Appendix 2A: Valued Graph Approach to the Shortest
Route Problem .........................................................................41
Appendix 2B: Estimating Travel Time Matrix by Google Maps API ....42
Chapter 3 Spatial Smoothing and Spatial Interpolation .....................................47
3.1 Spatial Smoothing ...................................................................47
3.1.1 Floating Catchment Area (FCA) Method ..................48
3.1.2 Kernel Density Estimation .........................................49
3.2 Point-Based Spatial Interpolation ............................................50
3.2.1 Global Interpolation Methods ....................................50
3.2.2 Local Interpolation Methods ......................................51
3.3 Case Study 3A: Mapping Place Names in Guangxi, China ......53
3.3.1 Part 1: Spatial Smoothing by the Floating
Catchment Area Method ............................................53
3.3.2 Part 2: Spatial Interpolation by Various Methods ......56
3.4 Area-Based Spatial Interpolation ............................................59
3.5 Case Study 3B: Area-Based Interpolations of Population
in Baton Rouge, Louisiana ......................................................60
3.5.1 Part 1. Using the Areal Weighting Interpolation
to Transform Data from Census Tracts to School
Districts in 2010 .........................................................60
3.5.2 Part 2. Using the Target-Density Weighting
(TDW) Interpolation to Interpolate Data from
Census Tracts in 2010 to Census Tracts in 2000 ........61
3.6 Summary .................................................................................64
Appendix 3A: Empirical Bayes Estimation for Spatial Smoothing .......64
Appendix 3B: Network Hierarchical Weighting Method for
Areal Interpolation ...................................................................65
Section ii Basic Quantitative Methods and
Applications
Chapter 4 GIS-Based Trade Area Analysis and Application in
Business Geography ...........................................................................69
4.1 Basic Methods for Trade Area Analysis ..................................70
4.1.1 Analog Method and Regression Models ....................70
4.1.2 Proximal Area Method ...............................................70
4.2 Gravity Models for Delineating Trade Areas ..........................72
4.2.1 Reilly’s Law ................................................................72
4.2.2 Huff Model .................................................................73
4.2.3 Link between Reilly’s Law and Huff Model ..............74
4.2.4 Extensions of the Huff Model ....................................75