Books  Data Analysis & Modelling  Cartography, Remote Sensing, Image Analysis & GIS 

Quantitative Methods and Applications in GIS

Out of Print

By: Fahui Wang

265 pages, diagrams

CRC Press

Hardback | Dec 2006 | #159425 | ISBN: 0849327954
Out of Print Details

About this book

Quantitative Methods and Applications in GIS integrates GIS, spatial analysis, and quantitative methods to address various issues in socioeconomic studies and public policy. Methods range from basic regression analysis to advanced topics such as linear programming and system of equations. Applications vary from typical themes in urban and regional analysis - trade area analysis, accessibility measures, analysis of regional growth patterns, land use simulation - to issues related to crime and health analyses.

The book covers common tasks such as distance and travel time estimation, spatial smoothing and interpolation, and accessibility measures. It also covers the major issues that are encountered in spatial analysis including modifiable areal unit problems, rate estimate of rare events in small populations, and spatial autocorrelation.

Each chapter has one subject theme, introduces the method (or a group of related methods) most relevant to the theme, and then uses case studies to implement the method in a GIS environment.


Contents

Getting Started with ArcGIS: Data Management and Basic Spatial Analysis ToolsSpatial and Attribute Data Management in ArcGISCase Study 1A: Mapping Population Density Pattern in Cuyahoga County, OhioSpatial Analysis Tools in ArcGIS: Queries, Spatial Joins and Map OverlaysCase Study 1B: Extracting Census Tracts in City of Cleveland and Analyzing Polygon AdjacencySummaryAppendix 1. Importing and Exporting ASCII Files in ArcGISMeasuring Distances and TimeMeasures of DistanceComputing Network Distance and TimeCase Study 2: Measuring Distances between Counties and Major Cities in Northeast ChinaSummaryAppendix 2. The Valued Graph Approach to the Shortest-Route ProblemSpatial Smoothing and Spatial InterpolationSpatial SmoothingCase Study 3A: Analyzing Tai Place-Names in Southern China by Spatial SmoothingPoint-Based Spatial InterpolationCase Study 3B: Surface Modeling and Mapping of Tai Place- Names in Southern ChinaArea-Based Spatial InterpolationCase Study 3C: Aggregating Data from Census Tracts to Neighborhoods and School Districts in Cleveland, OhioSummaryAppendix 3. Empirical Bayes (EB) Estimation for Spatial SmoothingGIS-Based Trade Area Analysis and Applications in Business Geography and Regional PlanningBasic Methods for Trade Area AnalysisGravity Models for Delineating Trade AreasCase Study 4A: Defining Fan Bases of Chicago Cubs and White SoxCase Study 4B: Defining Hinterlands of Major Cities in Northeast ChinaConcluding RemarksAppendix 4. Economic Foundation of the Gravity ModelGIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare AccessIssues on AccessibilityThe Floating Catchment Area MethodsThe Gravity-Based MethodCase Study 5: Measuring Spatial Accessibility to Primary Care Physician in Chicago RegionDiscussion and RemarksAppendix 5. A Property for Accessibility MeasuresFunction Fittings by Regressions and Application in Analyzing Urban and Regional Density PatternsThe Density Function Approach to Urban and Regional StructuresFunction Fittings for Monocentric ModelsNonlinear and Weighted Regressions in Function FittingsFunction Fittings for Polycentric ModelsCase Study 6: Analyzing Urban Density Patterns in Chicago RegionDiscussion and SummaryAppendix 6A: Deriving Urban Density FunctionsAppendix 6B: OLS Regression for a Linear Bivariate ModelAppendix 6C: Sample SAS Program for Monocentric Function FittingsPrincipal Components, Factor, and Cluster Analyses, and Application in Social Area AnalysisPrincipal Components and Factor AnalysisCluster AnalysisSocial Area AnalysisCase Study 7: Social Area Analysis in BeijingDiscussion and SummaryAppendix 7A. Discriminant Function AnalysisAppendix 7B. Sample SAS Program for Factor and Cluster AnalysesGeographic Approaches to Analysis of Rare Events in Small Population and Application in

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