Overview
- Includes the most up-to-date practices and research using big data in the field of city and regional planning for the smart city
- Increases the understanding of spatial-temporal analysis of human mobility and transportation, especially relevant to structures affected by the rapid urbanization process in China
- Explains how big data changes the thinking of planners and researchers in urban planning practice
- The first book to introduce big data-based research planning practices in China to planners, researchers and students
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Geographic Information Science (AGIS)
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Table of contents (22 chapters)
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Social Big Data for Exploring Human Behaviors and Urban Structure
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POI for Exploring Urban Space Recognition
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Mobile Device Data for Integrating Land Use and Transportation Planning
Keywords
- Geocomputing
- Data Management
- Urban Planning
- Regional Planning
- Smart City
- Bayesian Network
- Big Data
- Ecological Space Recognition
- Traffic Planning
- Origin Destination Flow
- Rail Network
- Urban transport
- Urban Structure
- Social Network Service
- Social Media Data
- Baidu
- water policy
- landscape/regional and urban planning
About this book
In the era of big data, this book explores the new challenges of urban-rural planning and management from a practical perspective based on a multidisciplinary project. Researchers as contributors to this book have accomplished their projects by using big data and relevant data mining technologies for investigating the possibilities of big data, such as that obtained through cell phones, social network systems and smart cards instead of conventional survey data for urban planning support. This book showcases active researchers who share their experiences and ideas on human mobility, accessibility and recognition of places, connectivity of transportation and urban structure in order to provide effective analytic and forecasting tools for smart city planning and design solutions in China.
Editors and Affiliations
About the editors
Zhenjiang Shen's research interests include policy-making support systems for planning and design using GIS & VR technology. He is serving as commissioner of Information Technology Education of Architectural Institute of Japan, and is a member of Scientific Committee of City Planning Institute of Japan. Dr. Shen also served as vice director, Urban Big data Commission, Chinese Society of Urban Studies. He is a member of Commission on Geospatial Analysis and Modeling of International Cartographic Association (ICA), and works as a joint member of Fudan University and PhD Instructor in Tsinghua University, China. Dr. Shen is editor-in-chief of IRSPSD International, managing editor of IJSSS and IJSSoc, and is General Director of International Community on Spatial Planning and Sustainable Development.
Miayoyi Li's research interests include spatial/urban planning, urban big data analysis, Geospatial analysis & Geo-simulations. He served as a researcher in the Information Center of Tsinghua Tongheng Planning & Design Institute (THUPDI), which is affiliated with the School of Architecture, Tsinghua University.Bibliographic Information
Book Title: Big Data Support of Urban Planning and Management
Book Subtitle: The Experience in China
Editors: Zhenjiang Shen, Miaoyi Li
Series Title: Advances in Geographic Information Science
DOI: https://doi.org/10.1007/978-3-319-51929-6
Publisher: Springer Cham
eBook Packages: Earth and Environmental Science, Earth and Environmental Science (R0)
Copyright Information: Springer International Publishing AG 2018
Hardcover ISBN: 978-3-319-51928-9Published: 06 October 2017
Softcover ISBN: 978-3-319-84780-1Published: 12 June 2018
eBook ISBN: 978-3-319-51929-6Published: 26 September 2017
Series ISSN: 1867-2434
Series E-ISSN: 1867-2442
Edition Number: 1
Number of Pages: XXX, 456
Number of Illustrations: 22 b/w illustrations, 232 illustrations in colour
Topics: Energy Policy, Economics and Management, Transportation, Water Policy/Water Governance/Water Management, Economic Geography, Landscape/Regional and Urban Planning, Data Mining and Knowledge Discovery