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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.
List of contents
Introduction. Literature Review. Study Area and Data. Monte Carlo Simulation Method. Commuting and Land Use. Wasteful Commuting. Conclusions. References
About the author
Yujie Hu is Assistant Professor of GIScience in the School of Geosciences at the University of South Florida in Tampa, Florida. He was a Research Fellow (2016-2017) with the Kinder Institute for Urban Research at Rice University in Houston, Texas. His research and teaching interests focus on the development and applications of GIS, spatial analysis, and visualization techniques in urban systems and public policy implications. The subjects of his research include transportation, public health, crime, and human-environment interactions. His research has been covered by the ABC 13 News of Houston and the Houston Public Media News, and supported by the Florida Sea Grant, Southeastern Association of State Highway and Transportation Officials (SASHTO), and the American Association of Geographers (AAG). He is a Board Member of the Transportation Geography Specialty Group of American Association of Geographers.
Fahui Wang is James J. Parsons Professor and Chair of the Department of Geography and Anthropology, Louisiana State University (LSU). His research focuses on applications of GIS and computational methods in human geography (including urban, transportation, economic, cultural and historical geography) and public policy (including urban planning, public health and public safety). His work has been supported by the National Science Foundation, U.S. Department of Energy, U.S. Department of Health and Human Services (Agency for Healthcare Research & Quality and the National Cancer Institute), U.S. Department of Housing and Urban Development, U.S. Department of Justice (National Institute of Justice and Office of Juvenile Justice and Delinquency Prevention), and the National Natural Science Foundation of China. He has published over 130 refereed articles and five books (including two edited books). He was a recipient of LSU Rainmaker Awards for outstanding research, scholarship and creative activity (2009, 2015) and LSU Distinguished Faculty Award (2018), and a Policy Winner of 2015 Outstanding Article of the Year from the Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services.
Summary
This book 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.
