Quantitative Methods and Socio-Economic Applications in GIS, Second Edition: 2nd Edition (Paperback) book cover

Quantitative Methods and Socio-Economic Applications in GIS, Second Edition

By Fahui Wang

© 2017 – CRC Press

350 pages

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pub: 2017-09-01
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About the Book

The second edition of a bestseller, Quantitative Methods and Socio-Economic Applications in GIS (previously titled Quantitative Methods and Applications in GIS) details applications of quantitative methods in social science, planning, and public policy with a focus on spatial perspectives. The book integrates GIS and quantitative (computational) methods and demonstrates them in various policy-relevant socio-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 related to socio-economic issues and public policy.

See What’s New in the Second Edition:

  • All project instructions are in ArcGIS 10.2 using geodatabase datasets
  • New chapters on regionalization methods and Monte Carlo simulation
  • Popular tasks automated as a convenient toolkit: Huff Model, 2SFCA accessibility measure, regionalization, Garin-Lowry model, and Monte Carlo based spatial simulation
  • Advanced tasks now implemented in user-friendly programs or ArcGIS: centrality indices, wasteful commuting measure, p-median problem, and traffic simulation

Each chapter has one subject theme and introduces the method (or a group of related methods) most relevant to the theme. While each method is illustrated in a special case of application, it can also be used to analyze different issues. For example, spatial regression is used to examine the relationship between job access and homicide patterns; systems of linear equations are analyzed to predict urban land use patterns; linear programming is introduced to solve the problem of wasteful commuting and allocate healthcare facilities; and Monte Carlo technique is illustrated in simulating urban traffic.

The book illustrates the range of computational methods and covers common tasks and major issues encountered in a spatial environment. It provides a platform for learning technical skills and quantitative methods in the context of addressing real-world problems, giving you instant access to the tools to resolve major socio-economic issues.

Table of Contents


Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools

Spatial and Attribute Data Management in ArcGIS

Spatial Analysis Tools in ArcGIS: Queries, Spatial Joins, and Map Overlays

Case Study 1: Mapping and Analyzing Population Density Pattern in Baton Rouge, Louisiana


Identifying Contiguous Polygons by Spatial Analysis Tools

Measuring Distance and Time

Measures of Distance

Computing Network Distance and Time

The Distance Decay Rule

Case Study 2: Computing Distances and Travel Time to Public Hospitals in Louisiana


A: The Valued Graph Approach to the Shortest Route Problem

B: Estimating Travel Time Matrix by Google Maps API

Spatial Smoothing and Spatial Interpolation

Spatial Smoothing

Point-Based Spatial Interpolation

Case Study 3A: Mapping Place Names in Guangxi, China

Area-Based Spatial Interpolation

Case Study 3B: Area-Based Interpolations of Population in Baton Rouge, Louisiana


A: Empirical Bayes Estimation for Spatial Smoothing

B: The Network Hierarchical Weighting Method for Areal Interpolation


GIS-Based Trade Area Analysis and Application in Business Geography

Basic Methods for Trade Area Analysis

Gravity Models for Delineating Trade Areas

Case Study 4A: Defining Fan Bases of Cubs and White Sox in Chicago Region

Case Study 4B: Estimating Trade Areas of Public Hospitals in Louisiana

Concluding Remarks

A: Economic Foundation of the Gravity Model

B: A Toolkit for Implementing the Huff Model

GIS-Based Measures of Spatial Accessibility and Application in Examining Health Care Access

Issues on Accessibility

The Floating Catchment Area Methods

The Gravity-Based and Generalized 2SFCA Models

Case Study 5: Measuring Spatial Accessibility to Primary Care Physicians in Chicago Region

Concluding Comments

A: A Property of Accessibility Measures

B: A Toolkit of Automated Spatial Accessibility Measures

Function Fittings by Regressions and Application in Analyzing Urban Density Patterns

The Density Function Approach to Urban and Regional Structures

Function Fittings for Monocentric Models

Nonlinear and Weighted Regressions in Function Fittings

Function Fittings for Polycentric Models

Case Study 6: Analyzing Urban Density Patterns in Chicago Urban Area

Discussions and Summary

A: Deriving Urban Density Functions

B: Centrality Measures and Association with Urban Densities

OLS Regression for a Linear Bivariate Model

Principal Components, Factor and Cluster Analyses, and Application in Social Area Analysis

Principal Components Analysis

Factor Analysis

Cluster Analysis

Social Area Analysis

Case Study 7: Social Area Analysis in Beijing

Discussions and Summary

Discriminant Function Analysis

Spatial Statistics and Applications

The Centrographic Measures

Case Study 8A: Measuring Geographic Distributions of Racial-Ethnic Groups in Chicago Urban Area

Spatial Cluster Analysis Based on Feature Locations

Case Study 8B: Spatial Cluster Analysis of Place Names in Guangxi, China

Spatial Cluster Analysis Based on Feature Values

Spatial Regression

Case Study 8C: Spatial Cluster and Regression Analyses of Homicide Patterns in Chicago


Spatial Filtering Methods for Regression Analysis


Regionalization Methods and Application in Analysis of Cancer Data

The Small Population Problem and Regionalization

The Spatial Order and the Modified Scale-Space Clustering (MSSC) Methods

The REDCAP Method

Case Study 9: Constructing Geographical Areas for Analysis of Late-Stage Breast Cancer Risks in the Chicago Region


A: The Poisson-Based Regression Analysis

B: A Toolkit of the Mixed-Level Regionalization Method

System of Linear Equations and Application of Garin-Lowry Model in Simulating Urban Population and Employment Patterns

System of Linear Equations

The Garin-Lowry Model

Case Study 10: Simulating Population and Service Employment Distributions in a Hypothetical City

Discussion and Summary

A: The Input-Output Model

B: Solving a System of Nonlinear Equations

A Toolkit for Calibrating the Garin- Lowry Model

Cellular Automata (CA) for Urban Land Use Modeling

Linear Programming and Applications in Examining Wasteful Commuting and Allocating Health Care Providers

Linear Programming and the Simplex Algorithm

Case Study 11A: Measuring Wasteful Commuting in Columbus, Ohio

Integer Programming and Location-Allocation Problems

Case Study 11B: Allocating Health Care Providers in Baton Rouge, Louisiana


A: Hamilton’s Model on Wasteful Commuting

B: Coding Linear Programming in SAS

A Programming Approach to Minimal Disparity in Accessibility

Monte Carlo Method and Its Application in Urban Traffic Simulation

Monte Carlo Simulation Method

Travel Demand Modeling

Examples of Monte Carlo-Based Spatial Simulation

Case Study 12: Monte Carlo-Based Traffic Simulation in Baton Rouge, Louisiana



Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General
POLITICAL SCIENCE / Public Policy / City Planning & Urban Development
TECHNOLOGY & ENGINEERING / Remote Sensing & Geographic Information Systems