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Big Data Support of Urban Planning and Management

The Experience in China

  • Zhenjiang Shen
  • Miaoyi Li

Part of the Advances in Geographic Information Science book series (AGIS)

Table of contents

  1. Front Matter
    Pages i-xxx
  2. Social Big Data for Exploring Human Behaviors and Urban Structure

  3. POI for Exploring Urban Space Recognition

  4. Mobile Device Data for Integrating Land Use and Transportation Planning

  5. Cyber Infrastructure for Urban Management

  6. Back Matter
    Pages 449-456

About this book

Introduction

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.

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

Editors and affiliations

  • Zhenjiang Shen
    • 1
  • Miaoyi Li
    • 2
  1. 1.Joint International FZUKU Lab SPSDFuzhou UniversityFuzhou CityChina
  2. 2.Joint International FZUKU Lab SPSDFuzhou UniversityFuzhou CityChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-51929-6
  • Copyright Information Springer International Publishing AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Earth and Environmental Science
  • Print ISBN 978-3-319-51928-9
  • Online ISBN 978-3-319-51929-6
  • Series Print ISSN 1867-2434
  • Series Online ISSN 1867-2442
  • Buy this book on publisher's site