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Computational Methods and GIS Applications in Social Science - Textbook and Lab Manual

ISBN-13: 9781032285184 / Mixed media product / 2023 / 602 str.

Lingbo Liu
Computational Methods and GIS Applications in Social Science - Textbook and Lab Manual Lingbo Liu 9781032285184 Taylor & Francis Ltd - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Computational Methods and GIS Applications in Social Science - Textbook and Lab Manual

ISBN-13: 9781032285184 / Mixed media product / 2023 / 602 str.

Lingbo Liu
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This set integrates GIS, spatial analysis, and computational methods for solving real-world problems in various policy-relevant social science applications. Thoroughly updated, this third edition, and its accompanying lab manual, showcase the best practices of spatial social science with step-by-step instructions in ArcGIS Pro and KNIME.

Kategorie:
Nauka, Socjologia i społeczeństwo
Wydawca:
Taylor & Francis Ltd
ISBN-13:
9781032285184
Rok wydania:
2023
Ilość stron:
602
Wymiary:
23.4 x 15.6
Oprawa:
Mixed media product

Textbook 

Part I: GIS and Basic Spatial Analysis Tasks  1. Getting Started with ArcGIS: Data Management and Basic Spatial Analysis Tools  2. Measuring Distance and Travel Time and Analyzing Distance Decay Behavior  3. Spatial Smoothing and Spatial Interpolation  Part II: Basic Computational Methods and Applications  4. Delineating Funcational Regions and Applications in Health Geography  5. GIS-bAsed Measures of Spatial Accessibility and Application in Examining Healthcare Disparity  6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns  7. Principal Compnents, Factor and Cluster Analyses and Application in Social Area Analysis  8. Spatial Statistics and Applications inCultural and Crime Geography  9. Regionalization Methods and Application in Analysis of Cancer Data  Part III: Advanced Computational Methods and Applications  10. System of Linear Equations and Application of Garin-Lowry in Simulating Urban Population and Employment Patterns  11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers  12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations  13. Agent-Based Model and Application in Crime Simulation  14. Spatiotemporal Big Data Analytics and Application in Urban Studies

Lab Manual

1. Getting Started with KNIME and Its Geospatial Analytics Extension  2. Measuring Distance and Time and Analyzing Distance Decay Behavior  3. Spatial Smoothing and Spatial Interpolation  4. Delineating Functional Regions and Application in Health Geography  5. GIS-Based Measure of Spatial Accessibility and Application in Examining Healthcare Disparity  6. Function Fittings by Regressions and Application in Analyzing Urban Density Patterns  7. Principal Components, Factor Analysis and Cluster Analysis and Application in Social Area Analysis  8. Spatial Statistics and Applications  9. Regionalization Methods and Applications in Analysis of Cancer Data  10. System of Linear Equations and Application of Garin-Lowry Model in Simulating Urban Population and Employment Patterns  11. Linear and Quadratic Programming and Applications in Examining Wasteful Commuting and Allocating Healthcare Providers  12. Monte Carlo Method and Applications in Urban Population and Traffic Simulations  13. Agent-Based Model and Application in Crime Simulation  14. Spatiotemporal Big Data Analytics and Applications in Urban Studies

Fahui Wang is Associate Dean of the Pinkie Gordon Lane Graduate School and Cyril & Tutta Vetter Alumni Professor in the Department of Geography and Anthropology, Louisiana State University. He earned a BS degree in geography from Peking University, China, and an MA degree in economics and a PhD in city and regional planning from the Ohio State University. His research has revolved around the broad theme of spatially integrated computational social sciences, public policy and planning in Geographic Information Systems. He is among the top 1% most-cited researchers in geography in the world.

Lingbo Liu is a postdoctoral fellow at the Center for Geographic Analysis, Harvard University, leading the development of Geospatial Analytics Extension for KNIME. He was a lecturer at the Department of Urban Planning, School of Urban Design, Wuhan University from 2005 to 2022, and obtained his PhD in Digital Urban Administration and Planning from Wuhan University in 2018. His research uses multi-source data and quantitative models to capture the spatiotemporal features of urban systems, and provides decision support for public policy, sustainable urban planning, and design.

 



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