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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.
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.
The Texas Department of Transportation funded Project 0-5345 to reach a better understanding of intercity commute patterns in Texas and to find regional public transportation solutions for intercity commuting problems. The project's interdisciplinary research team came from Texas Southern University, Texas State University-San Marcos, Texas Transportation Institute (TTI), and Prairie View A & M University. This report summarizes the research activities and accomplishments of the project regarding travel corridors and geographic information system (GIS) commute models, including: (1) development of a set of GIS-based analysis models for the identification of intercity commuting patterns and travel corridors in central Texas; (2) examination of commuting patterns between rural communities and urban areas as well as commuting flows between different counties (cities) in a five-county study area in central Texas based on U.S. 2000 Census Journey-to-Work data; (3) identification of traffic corridors that carry a significant amount of intercity and rural-to-urban traffic in the study area based on U.S. 2000 Census Journey-to-Work data and 2005 TTI external travel survey data; and (4) identification of rural communities that generated the largest numbers of commuting traffic and road segments that carried a high volume of traffic. The research team found that the GIS-based analysis models are effective for analyzing commuting patterns and travel corridors. Commute flows between urban and rural areas account for about 20 percent of the total commute traffic in the study area, and inter-county commute accounts for 13 percent of the total commute traffic.
By understanding the movement patterns of people, mathematical modelers can develop models that can better analyze and predict the spread of infectious diseases. People can come into close contact in their workplaces. This report describes methods to develop georeferenced commuting patterns that can be used to characterize the work-related movement of US populations and help agent-based modelers predict workplace contacts that result in disease transmission. We used a census data product called "Census Spatial Tabulation: Census Track of Work by Census Tract of Residence (STP64)" as the data source to develop commuting pattern data for agent-based synthesized populations databases and to develop map products to visualize commuting patterns in the United States. The three primary maps we developed show inbound, outbound, and net change levels of inbound versus outbound commuters by census tract for the year 2000. Net change counts of commuters are visualized as elevations. The results can be used to quantify and assign commuting patterns of synthesized populations among different census tracts.
This book provides a comprehensive discussion on urban growth and sprawl, and how they can be analyzed using remote sensing imageries. It compiles views of numerous researchers that help in understanding the urban growth and sprawl; their patterns, process, causes, consequences, and countermeasures; how remote sensing data and geographic information system techniques can be used in mapping, monitoring, measuring, analyzing, and simulating the urban growth and sprawl and what are the merits and demerits of available methods and models. This book will be of value for the scientists and researchers engaged in urban geographic research, especially using remote sensing imageries. This book will serve as a rigours literature review for them. Post graduate students of urban geography or urban/regional planning may refer this book as additional studies. This book may help the academicians for preparing lecture notes and delivering lectures. Industry professionals may also be benefited from the discussed methods and models along with numerous citations.
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.