Commuting, the daily link between residences and workplaces, sets up the complex interaction between the two most important land uses (residential and employment) in a city, and dictates the configuration of urban structure. In addition to prolonged time and stress for individual commuters on traffic, commuting comes with additional societal costs including elevated crash risks, worsening air quality, and louder traffic noise, etc. These issues are important to city planners, policy researchers, and decision makers. GIS-Based Simulation and Analysis of Intra-Urban Commuting, presents GIS-based simulation, optimization and statistical approaches to measure, map, analyze, and explain commuting patterns including commuting length and efficiency. Several GIS-automated easy-to-use tools will be available, along with sample data, for readers to download and apply to their own studies. This book recognizes that reporting errors from survey data and use of aggregated zonal data are two sources of bias in estimation of wasteful commuting, it studies the temporal trend of intraurban commuting pattern based on the most recent period newly-available 2006-2010, and it focuses on commuting, and especially wasteful commuting within US cities. It includes ready-to-download GIS-based simulation tools and sample data, and an explanation of optimization and statistical techniques of how to measure commuting, as well as presenting a methodology that can be applicable to other studies. This book is an invaluable resource for students, researchers, and practitioners in geography, urban planning, public policy, transportation engineering, and other related disciplines.

Hospital service areas (HSAs) and hospital referral regions (HRRs) are considered more appropriate units than geopolitical units for analyzing the performance of health care markets and policy implementation. GIS Automated Delineation of Hospital Service Areas represents the state-of-the-art approach in delineating HSAs and HRRs by using GIS-automated processes. It provides the best practices for defining such areas scientifically, in a geographically accurate manner, and without a steep learning curve. This book is intended to mainly serve professionals in geography, urban and regional planning, public health, and related fields. It is also useful for scholars in the above fields who have research interests related to GIS and spatial analysis applications in health care. It can be used as a supplemental text for upper-level undergraduate and graduate students in courses related to GIS and public health. Features: Introduces innovative state-of-the-art methods for delineation of HSAs (Dartmouth method, Huff model, network community detection methods) Provides best practices and one-stop solution for related data processing tasks (e.g., distance and travel time estimation, identifying the best-fitting distance decay function) Automates the methods in ArcGIS Pro toolkits Includes free ready-to-download GIS tools and sample data available on authors’ website Presents a methodology that is applicable to delineation of other service areas, catchment areas or functional regions for business analysis, planning, and public policy studies

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. 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.

This lab manual is a companion to the third edition of the textbook Computational Methods and GIS Applications in Social Science. It uses the open-source platform KNIME to illustrate a step-by-step implementation of each case study in the book. KNIME is a workflow-based platform supporting visual programming and multiple scripting language such as R, Python, and Java. The intuitive, structural workflow not only helps students better understand the methodology of each case study in the book, but also enables them to easily replicate, transplant and expand the workflow for further exploration with new data or models. This lab manual could also be used as a GIS automation reference for advanced users in spatial analysis. FEATURES The first hands-on, open-source KNIME lab manual written in tutorial style and focused on GIS applications in social science Includes 22 case studies from the United States and China that parallel the methods developed in the textbook Provides clear step-by-step explanations on how to use the open-source platform KNIME to understand basic and advanced analytical methods through real-life case studies Enables readers to easily replicate and expand their work with new data and models A valuable guide for students and practitioners worldwide engaged in efforts to develop GIS automation in spatial analysis This lab manual is intended for upper-level undergraduate and graduate students taking courses in quantitative geography, spatial analysis, GIS applications in socioeconomic studies, GIS applications in business, and location theory, as well as researchers in the similar fields of geography, city and regional planning, sociology, and public administration.

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

This book is a practical guide on how to design, create and validate a spatial microsimulation model. These models are becoming more popular as academics and policy makers recognise the value of place in research and policy making. Recent spatial microsimulation models have been used to analyse health and social disadvantage for small areas; and to look at the effect of policy change for small areas. This provides a powerful analysis tool for researchers and policy makers. This book covers preparing the data for spatial microsimulation; a number of methods for both static and dynamic spatial microsimulation models; validation of the models to ensure the outputs are reasonable; and the future of spatial microsimulation. The book will be an essential handbook for any researcher or policy maker looking to design and create a spatial microsimulation model. This book will also be useful to those policy makers who are commissioning a spatial microsimulation model, or looking to commission work using a spatial microsimulation model, as it provides information on the different methods in a non-technical way.

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.