2nd Edition

Quantitative Methods and Socio-Economic Applications in GIS

By Fahui Wang Copyright 2015
    334 Pages
    by CRC Press

    334 Pages 99 B/W Illustrations
    by CRC Press

    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.

    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


    Fahui Wang