Big Data for Regional Science: Routledge Advances in Regional Economics, Science and Policy
Editat de Laurie A Schintler, Zhenhua Chenen Limba Engleză Paperback – 12 dec 2019
This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes contributed by experts from all over the world with a wide array of disciplinary backgrounds. The content is organized along four themes: sources of big data; integration, processing and management of big data; analytics for big data; and, higher level policy and programmatic considerations. As well as concisely and comprehensively synthesising work done to date, the book also considers future challenges and prospects for the use of big data in regional science.
Big Data for Regional Science provides a seminal contribution to the field of regional science and will appeal to a broad audience, including those at all levels of academia, industry, and government.
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Specificații
ISBN-13: 9780367885694
ISBN-10: 0367885697
Pagini: 376
Dimensiuni: 156 x 234 x 24 mm
Greutate: 0.7 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Seria Routledge Advances in Regional Economics, Science and Policy
Locul publicării:Oxford, United Kingdom
ISBN-10: 0367885697
Pagini: 376
Dimensiuni: 156 x 234 x 24 mm
Greutate: 0.7 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Seria Routledge Advances in Regional Economics, Science and Policy
Locul publicării:Oxford, United Kingdom
Public țintă
Postgraduate and UndergraduateCuprins
Contents
List of Figures
List of Tables
List of Contributors
Foreword by Michael Batty
1. Introduction
Laurie A. Schintler and Zhenhua Chen
PART I New Big Data Source in Regional Science
2. Opportunities for Retail Data and Their Geographic Integration in Social Science
Guy Lansley and Paul Longley
3. Use of Probe Data Generated by Taxis
Josep Maria Salanova, Michal Maciejewski, Joschka Bischoff, Miquel Estrada Romeu, Panagiotis Tzenos, and Iraklis Stamos
4. The Emerging Geography of Globalizing Chinese Cities Based on Web-based Information Services
Jean-Claude Thill, Jae Soen Son, and Min Chen
5. Using Web Crawled Data for Urban Housing Research
Zhenhua Chen
6. Examining Intraurban Migration in the Twin Cities Metropolitan Area using Parcel Data
Shipeng Sun
7. Crowdsourcing Street Beauty: Visual Preference Surveys in the Big Data Era
Robert Goodspeed and Xiang Yan
8. Public Response to Campus Shootings Using Social Media
Xinyue Ye, Zhuo Chen, and Shengwen Li
PART II Big Data Integration and Management
9. Using Big (Synthetic) Data to Identify Local Housing Market Attributes
A.Yair Grinberger and Daniel Felsenstein
10. Using Recurrent Spatio-Temporal Profiles in GPS Panel Data for Enhancing Imputation of Activity Type
Tao Feng and Harry J.P. Timmermans
11. Processing Uncertain GPS Trajectory Data for Assessing the Locations of Physical Activity
Sungsoon Hwang, Sai Yalla, and Ryan Crews
12. Exploring Digital Technology Industry Clusters Using Administrative and Frontier Data
Max Nathan and Anna Rosso
13. The Integration of Internet Data and Census Data for Spatial Analysis in a
List of Figures
List of Tables
List of Contributors
Foreword by Michael Batty
1. Introduction
Laurie A. Schintler and Zhenhua Chen
PART I New Big Data Source in Regional Science
2. Opportunities for Retail Data and Their Geographic Integration in Social Science
Guy Lansley and Paul Longley
3. Use of Probe Data Generated by Taxis
Josep Maria Salanova, Michal Maciejewski, Joschka Bischoff, Miquel Estrada Romeu, Panagiotis Tzenos, and Iraklis Stamos
4. The Emerging Geography of Globalizing Chinese Cities Based on Web-based Information Services
Jean-Claude Thill, Jae Soen Son, and Min Chen
5. Using Web Crawled Data for Urban Housing Research
Zhenhua Chen
6. Examining Intraurban Migration in the Twin Cities Metropolitan Area using Parcel Data
Shipeng Sun
7. Crowdsourcing Street Beauty: Visual Preference Surveys in the Big Data Era
Robert Goodspeed and Xiang Yan
8. Public Response to Campus Shootings Using Social Media
Xinyue Ye, Zhuo Chen, and Shengwen Li
PART II Big Data Integration and Management
9. Using Big (Synthetic) Data to Identify Local Housing Market Attributes
A.Yair Grinberger and Daniel Felsenstein
10. Using Recurrent Spatio-Temporal Profiles in GPS Panel Data for Enhancing Imputation of Activity Type
Tao Feng and Harry J.P. Timmermans
11. Processing Uncertain GPS Trajectory Data for Assessing the Locations of Physical Activity
Sungsoon Hwang, Sai Yalla, and Ryan Crews
12. Exploring Digital Technology Industry Clusters Using Administrative and Frontier Data
Max Nathan and Anna Rosso
13. The Integration of Internet Data and Census Data for Spatial Analysis in a
Notă biografică
Laurie A. Schintler is a computational social scientist with interests and research activity in the following areas related to Big Data analytics: geocomputation (socio-spatio modelling), transportation, regional science, scientometrics/bibliometrics and network modeling and analysis. She also has expertise on the policy-side of Big Data - specifically, issues related to the digital divide, job automation, workforce education and training and emerging technologies.
Zhenhua Chen is an assistant professor in City and Regional Planning at the Knowlton School of Architecture at The Ohio State University. His research interest includes regional science, big data analytics, risk and resilience, infrastructure planning and policy.
Zhenhua Chen is an assistant professor in City and Regional Planning at the Knowlton School of Architecture at The Ohio State University. His research interest includes regional science, big data analytics, risk and resilience, infrastructure planning and policy.
Descriere
This book provides a comprehensive, multidisciplinary and cutting-edge perspective on big data for regional science. Chapters contain a collection of research notes by experts from all over the world with a wide array of disciplinary backgrounds.