Seeing Cities Through Big Data: Research, Methods and Applications in Urban Informatics (Springer Geography)
Language: English
Published by Springer, 2016
- Hardcover
- New

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- Title
- Seeing Cities Through Big Data: Research, Methods and Applications in Urban Informatics (Springer Geography)
- Publisher
- Springer
- Publication year
- 2016
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 331940900X
- ISBN 13
- 9783319409009
- Item weight
- 1,088 grams
- Series
- Book 34 of 84: Springer Geography
This book introduces the latest thinking on the use of Big Data in the context of urban systems, including research and insights on human behavior, urban dynamics, resource use, sustainability and spatial disparities, where it promises improved planning, management and governance in the urban sectors (e.g., transportation, energy, smart cities, crime, housing, urban and regional economies, public health, public engagement, urban governance and political systems), as well as Big Data’s utility in decision-making, and development of indicators to monitor economic and social activity, and for urban sustainability, transparency, livability, social inclusion, place-making, accessibility and resilience.
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About the Author
Nebiyou Tilahun is an Assistant Professor in the Urban Planning and Policy department at University of Illinois at Chicago. He earned his PhD in Civil Engineering from the University of Minnesota in 2010. He was previously a postdoctoral researcher at the Humphrey School for Public Affairs and at the Urban Transportation Center at University of Illinois at Chicago. His work focuses on travel behavior analyses, transportation planning models, and social issues surrounding transportation. His recent works includes the evaluation of last-mile barriers to intermodal transportation and on strategies to enhance transit accessibility in regions implementing transit system changes. He is also interested in the use of agent-based models for transportation planning applications and is the developer of ABODE (an agent based trip distribution model for work purposes). His research leverages large datasets collected by public and private institutions to inform questions about traveller’s long and short-term decisions for location and mode as well as to understand urban transit and land use related issues to inform transportation policy. He received the 2008 Matthew J. Huber Award for Excellence in Transportation Research and Education from the University of Minnesota’s Center for Transportation Studies.
Moira Zellner joined the Urban Planning & Policy Program as an Assistant Professor in January of 2006. Born in Buenos Aires, Argentina, Moira earned her undergraduate degree in ecology at the Centro de Altos Estudios en Ciencias Exactas, and pursued graduate studies in urban and regional planning and in complex systems at the University of Michigan. Before coming to the US, she worked in Argentina as a consultant on environmental issues for local and international environmental engineering firms and for the undersecretary of Environment in the City of Buenos Aires, in projects related to domestic and hazardous waste management, river remediation, industrial pollution control, and environmental impact assessments. She also participated in interdisciplinary andinternational research projects of urban air pollution and of the spread of tuberculosis through public transportation. In the US, her professional work includes greenway development and river restoration projects in Miami Beach and in California, and transportation surveys. Her current research involves assessing the environmental impacts of urbanization, and exploring how to enhance the sustainability and resilience of urban areas. The focus is on how specific policy and behavioral changes can effectively address complex environmental problems, in which decentralized decisions result in regional land-use and consumption patterns that negatively affect resource availability and quality. Her research also examines the applicability of complexity theory and complexity-based models to policy exploration and social learning.
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Ria Christie Collections
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