Big data for regional science /
edited by Laurie A. Schintler and Zhenhua Chen.
- 1 online resource (xxv, 350 pages)
chapter 1 Introduction / part Part I New big data sources in regional science -- chapter 2 Opportunities for retail data and their geographic integration in social science / chapter 3 Use of probe data generated by taxis / chapter 4 The emerging geography of globalizing Chinese cities based on web-based information services / chapter 5 Using web-crawled data for urban housing research / chapter 6 Examining intraurban migration in the Twin Cities metropolitan area using parcel data / chapter 7 Crowdsourcing street beauty: Visual preference surveys in the big data era / chapter 8 Public response to campus shootings using social media / part Part II Big data integration and management -- chapter 9 Using big (synthetic) data to identify local housing market attributes / chapter 10 Using recurrent spatio-temporal profiles in GPS panel data for enhancing imputation of activity type / chapter 11 Processing uncertain GPS trajectory data for assessing the locations of physical activity / chapter 12 Exploring digital technology industry clusters using administrative and frontier data / chapter 13 The integration of Internet data and census data for spatial analysis in a geoportal / chapter 14 Big data, socio-environmental resilience and urban systems planning support / chapter 15 Big data perspectives: Adoption of a regional environmental information system / part Part III Big data analytics in regional science -- chapter 16 From ‘big data’ to big regions: The geography of the American commute / chapter 17 Big data, agents and the city / chapter 18 Damage assessment of the urban environment during disasters using volunteered geographic information / chapter 19 Integrating big data into a geospatial framework of disaster impact analysis / chapter 20 A big data application of spatial microsimulation for neighborhoods in England and Wales / chapter 21 Big data clustering and its applications in regional science / chapter 22 Big data and shrinking cities: How Twitter can help determine urban sentiments / part Part IV New frontiers of big data in regional science -- chapter 23 Big data in emerging cities / chapter 24 Recommendations for big data programs at transportation agencies / chapter 25 Towards data-driven cities: Incorporating big data into urban management / chapter 26 Big data, privacy and the policy process in the United States: In regional economic development / chapter 27 Urban informatics: Defining an emerging field / chapter 28 The constantly shifting face of the digital divide: Implications for big data, urban informatics and regional science / LAURIE A. SCHINTLER -- GUY LANSLEY -- JOSEP MARIA SALANOVA, MICHAL MACIEJEWSKI, JOSCHKA BISCHOFF, -- JEAN-CLAUDE THILL, JAE SOEN SON AND MIN CHEN -- ZHENHUA CHEN -- SHIPENG SUN -- ROBERT GOODSPEED -- XINYUE YE -- A. YAIR GRINBERGER AND DANIEL FELSENSTEIN -- TAO FENG AND HARRY J.P. TIMMERMANS -- SUNGSOON HWANG -- MAX NATHAN -- BING SHE -- BRIAN DEAL -- ANDREA DE MONTIS, SABRINA LAI, NICOLETTA SANNIO AND -- ALASDAIR RAE -- ANDREW CROOKS -- CAROLYNNE HULTQUIST -- YURI MANSURY -- MICHELLE A. MORRIS -- YAZHOU REN -- JUSTIN B. HOLLANder -- PRANAB K. ROY CHOWDHURY, SUSANNA H. SUTHERLAND, KATHLEEN -- GREGORY D. ERHARDT -- HOSSEIN ESTIRI -- ROGER STOUGH -- ROBERT GOODSPEED -- LAURIE A. SCHINTLER.
"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.
9781315270838 9781351983242
10.4324/9781315270838 doi
Regional planning--Statstical methods.
City planning--Statistical methods.
Big data.
HT391 / .B468 2018
307.120727 / B592
chapter 1 Introduction / part Part I New big data sources in regional science -- chapter 2 Opportunities for retail data and their geographic integration in social science / chapter 3 Use of probe data generated by taxis / chapter 4 The emerging geography of globalizing Chinese cities based on web-based information services / chapter 5 Using web-crawled data for urban housing research / chapter 6 Examining intraurban migration in the Twin Cities metropolitan area using parcel data / chapter 7 Crowdsourcing street beauty: Visual preference surveys in the big data era / chapter 8 Public response to campus shootings using social media / part Part II Big data integration and management -- chapter 9 Using big (synthetic) data to identify local housing market attributes / chapter 10 Using recurrent spatio-temporal profiles in GPS panel data for enhancing imputation of activity type / chapter 11 Processing uncertain GPS trajectory data for assessing the locations of physical activity / chapter 12 Exploring digital technology industry clusters using administrative and frontier data / chapter 13 The integration of Internet data and census data for spatial analysis in a geoportal / chapter 14 Big data, socio-environmental resilience and urban systems planning support / chapter 15 Big data perspectives: Adoption of a regional environmental information system / part Part III Big data analytics in regional science -- chapter 16 From ‘big data’ to big regions: The geography of the American commute / chapter 17 Big data, agents and the city / chapter 18 Damage assessment of the urban environment during disasters using volunteered geographic information / chapter 19 Integrating big data into a geospatial framework of disaster impact analysis / chapter 20 A big data application of spatial microsimulation for neighborhoods in England and Wales / chapter 21 Big data clustering and its applications in regional science / chapter 22 Big data and shrinking cities: How Twitter can help determine urban sentiments / part Part IV New frontiers of big data in regional science -- chapter 23 Big data in emerging cities / chapter 24 Recommendations for big data programs at transportation agencies / chapter 25 Towards data-driven cities: Incorporating big data into urban management / chapter 26 Big data, privacy and the policy process in the United States: In regional economic development / chapter 27 Urban informatics: Defining an emerging field / chapter 28 The constantly shifting face of the digital divide: Implications for big data, urban informatics and regional science / LAURIE A. SCHINTLER -- GUY LANSLEY -- JOSEP MARIA SALANOVA, MICHAL MACIEJEWSKI, JOSCHKA BISCHOFF, -- JEAN-CLAUDE THILL, JAE SOEN SON AND MIN CHEN -- ZHENHUA CHEN -- SHIPENG SUN -- ROBERT GOODSPEED -- XINYUE YE -- A. YAIR GRINBERGER AND DANIEL FELSENSTEIN -- TAO FENG AND HARRY J.P. TIMMERMANS -- SUNGSOON HWANG -- MAX NATHAN -- BING SHE -- BRIAN DEAL -- ANDREA DE MONTIS, SABRINA LAI, NICOLETTA SANNIO AND -- ALASDAIR RAE -- ANDREW CROOKS -- CAROLYNNE HULTQUIST -- YURI MANSURY -- MICHELLE A. MORRIS -- YAZHOU REN -- JUSTIN B. HOLLANder -- PRANAB K. ROY CHOWDHURY, SUSANNA H. SUTHERLAND, KATHLEEN -- GREGORY D. ERHARDT -- HOSSEIN ESTIRI -- ROGER STOUGH -- ROBERT GOODSPEED -- LAURIE A. SCHINTLER.
"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.
9781315270838 9781351983242
10.4324/9781315270838 doi
Regional planning--Statstical methods.
City planning--Statistical methods.
Big data.
HT391 / .B468 2018
307.120727 / B592