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Ad Functionality Blocked
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This textbook integrates GIS, spatial analysis, and computational methods for solving real-world problems in various policy-relevant social science applications. Thoroughly updated, the third edition showcases the best practices of computational spatial social science and includes numerous case studies with step-by-step instructions in ArcGIS Pro and open-source platform KNIME. Readers sharpen their GIS skills by applying GIS techniques in detecting crime hotspots, measuring accessibility of primary care physicians, forecasting the impact of hospital closures on local community, or siting the best locations for business. Google launched the Google Maps API, a JavaScript API, to allow customization of online maps in 2005. The Google Maps API enables one to estimate the travel time without reloading the web page or displaying portions of the map. An earlier version of the Python program was developed to use the Google Maps API for computing an OD travel time matrix. An improved version GoogleODTravelTimePro.py by Wang and Wang, available under the subfolder Scripts, is used here to illustrate its usage. The program reads the origin (O) and destination (D) layers of point or polygon features in a projected coordinate system and automatically calculates the latitudes and longitudes of all features by their point locations or geographic centroids of the polygons. The data are fed into a tool in Python that automates the process of estimating the travel time and distance matrix between a set of origins and a set of destinations at a time by calling the Google Maps Distance Matrix API. Features: Fully updated using the latest version of ArcGIS Pro and open-source platform KNIME Features two brand-new chapters on agent-based modeling and big data analytics Provides newly automated tools for regionalization, functional region delineation, accessibility measures, planning for maximum equality in accessibility, and agent-based crime simulation Includes many compelling examples and real-world case studies related to social science, urban planning, and public policy Provides a website for downloading data and programs for implementing all case studies included in the book and the KNIME lab manual Intended for students taking upper-level undergraduate and graduate-level courses in quantitative geography, spatial analysis, and GIS applications, as well as researchers and professionals in fields such as geography, city and regional planning, crime analysis, public health, and public administration. Preface PART I GIS and Basic Spatial Analysis Tasks Chapter 1 Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools Chapter 2 Measuring Distance and Travel Time and Analyzing Distance Decay Behavior Chapter 3 Spatial Smoothing and Spatial Interpolation PART II Basic Computational Methods and Applications Chapter 4 Delineating Functional Regions and Application in Health Geography Chapter 5 GIS-Based Measures of Spatial Accessibility and Application in Examining Healthcare Disparity Chapter 6 Function Fittings by Regressions and Application in Analyzing Urban Density Patterns Chapter 7 Principal Components, Factor Analysis, and Cluster Analysis and Application in Social Area Analysis Chapter 8 Spatial Statistics and Applications Chapter 9 Regionalization Methods and Application in Analysis of Cancer Data Chapter 10 System of Linear Equations and Application of the Garin–Lowry Model in Simulating Urban Population and Employment Patterns Chapter 11 Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers Chapter 12 Monte Carlo Method and Applications in Urban Population and Traffic Simulations Chapter 13 Agent-Based Model and Application in Crime Simulation Chapter 14 Spatiotemporal Big Data Analytics and Applications in Urban Studies