Big data for regional science - Chen, Zhenhua (Writer on public policy); Schintler, Laurie A. (Laurie Anne) (Abingdon, Oxon ; New York, NY : Routledge, 2018)
"Recent technological advancements and other related factors and trends are contributing to the production of an astoundingly large and rapidly accelerating collection of data, or'Big Data'. This data now allows us to examine urban and regional phenomena in ways that were previously not possible. Despite the tremendous potential of big data for regional science, its use and application in this context is fraught with issues and challenges. This book brings together leading contributors to present an interdisciplinary, agenda-setting and action-oriented platform for research and practice in the urban and regional community. 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. "--Provided by publisher.
chapter 1 Introduction / LAURIE A. SCHINTLER -- part Part I New big data sources in regional science -- chapter 2 Opportunities for retail data and their geographic integration in social science / GUY LANSLEY -- chapter 3 Use of probe data generated by taxis / JOSEP MARIA SALANOVA, MICHAL MACIEJEWSKI, JOSCHKA BISCHOFF, -- chapter 4 The emerging geography of globalizing Chinese cities based on web-based information services / JEAN-CLAUDE THILL, JAE SOEN SON AND MIN CHEN -- chapter 5 Using web-crawled data for urban housing research / ZHENHUA CHEN -- chapter 6 Examining intraurban migration in the Twin Cities metropolitan area using parcel data / SHIPENG SUN -- chapter 7 Crowdsourcing street beauty: Visual preference surveys in the big data era / ROBERT GOODSPEED -- chapter 8 Public response to campus shootings using social media / XINYUE YE -- part Part II Big data integration and management -- chapter 9 Using big (synthetic) data to identify local housing market attributes / A. YAIR GRINBERGER AND DANIEL FELSENSTEIN -- chapter 10 Using recurrent spatio-temporal profiles in GPS panel data for enhancing imputation of activity type / TAO FENG AND HARRY J.P. TIMMERMANS -- chapter 11 Processing uncertain GPS trajectory data for assessing the locations of physical activity / SUNGSOON HWANG -- chapter 12 Exploring digital technology industry clusters using administrative and frontier data / MAX NATHAN -- chapter 13 The integration of Internet data and census data for spatial analysis in a geoportal / BING SHE -- chapter 14 Big data, socio-environmental resilience and urban systems planning support / BRIAN DEAL -- chapter 15 Big data perspectives: Adoption of a regional environmental information system / ANDREA DE MONTIS, SABRINA LAI, NICOLETTA SANNIO AND -- part Part III Big data analytics in regional science -- r
Keywords: Regional planning -- Statstical methods; City planning -- Statistical methods; Big data