Big Data for Regional Science

ISBN-13: 9780367885694 / Angielski / Miękka / 2019 / 350 str.

Laurie A. Schintler; Zhenhua Chen

Opis

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.

Spis treści

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

O autorze

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.