MARC Record from marc_columbia

LEADER: 06594cam a2200697Ii 4500
001 15123678
005 20220604234046.0
006 m o d
007 cr cn|||||||||
008 170810s2018 enk ob 001 0 eng d
035 $a(OCoLC)ocn993951285
035 $a(NNC)15123678
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019 $a1000433427$a1058643444
020 $a9781315270838$q(electronic bk.)
020 $a1315270838$q(electronic bk.)
020 $a9781351983266
020 $a1351983261
020 $a9781351983242
020 $a1351983245
020 $z9781138282186$q(hardback)
020 $z1138282189$q(hardback)
035 $a(OCoLC)993951285$z(OCoLC)1000433427$z(OCoLC)1058643444
050 4 $aHT391$b.B468 2018eb
072 7 $aSOC$x026030$2bisacsh
082 04 $a307.1/20727$223
049 $aZCUA
245 00 $aBig data for regional science /$cedited by Laurie A Schintler and Zhenhua Chen.
250 $aFirst edition.
264 1 $aLondon :$bRoutledge,$c2018.
300 $a1 online resource (xxv, 350 pages)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aRoutledge Advances in Regional Economics, Science and Policy
504 $aIncludes bibliographical references and index.
505 0 $aCover; Title; Copyright; Contents; List of figures; List of tables; List of contributors; Foreword; 1 Introduction; Part I New big data sources in regional science; 2 Opportunities for retail data and their geographic integration in social science; 3 Use of probe data generated by taxis; 4 The emerging geography of globalizing Chinese cities based on web-based information services; 5 Using web-crawled data for urban housing research; 6 Examining intraurban migration in the Twin Cities metropolitan area using parcel data.
505 8 $a7 Crowdsourcing street beauty: Visual preference surveys in the big data era8 Public response to campus shootings using social media; Part II Big data integration and management; 9 Using big (synthetic) data to identify local housing market attributes; 10 Using recurrent spatio-temporal profiles in GPS panel data for enhancing imputation of activity type; 11 Processing uncertain GPS trajectory data for assessing the locations of physical activity; 12 Exploring digital technology industry clusters using administrative and frontier data.
505 8 $a13 The integration of Internet data and census data for spatial analysis in a geoportal14 Big data, socio-environmental resilience and urban systems planning support; 15 Big data perspectives: Adoption of a regional environmental information system; Part III Big data analytics in regional science; 16 From 'big data' to big regions: The geography of the American commute; 17 Big data, agents and the city; 18 Damage assessment of the urban environment during disasters using volunteered geographic information; 19 Integrating big data into a geospatial framework of disaster impact analysis.
505 8 $a20 A big data application of spatial microsimulation for neighborhoods in England and Wales21 Big data clustering and its applications in regional science; 22 Big data and shrinking cities: How Twitter can help determine urban sentiments; Part IV New frontiers of big data in regional science; 23 Big data in emerging cities; 24 Recommendations for big data programs at transportation agencies; 25 Towards data-driven cities: Incorporating big data into urban management; 26 Big data, privacy and the policy process in the United States: In regional economic development.
505 8 $a27 Urban informatics: Defining an emerging field28 The constantly shifting face of the digital divide: Implications for big data, urban informatics and regional science; Index.
520 2 $a"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.
650 0 $aRegional planning.
650 0 $aCity planning$xStatistical methods.
650 0 $aBig data.
650 6 $aAménagement du territoire.
650 6 $aDonnées volumineuses.
650 7 $aregional planning.$2aat
650 7 $aSOCIAL SCIENCE$xSociology$xUrban.$2bisacsh
650 07 $aBUSINESS & ECONOMICS$xDevelopment$xEconomic Development.$2bisacsh
650 7 $aBig data.$2fast$0(OCoLC)fst01892965
650 7 $aCity planning$xStatistical methods.$2fast$0(OCoLC)fst00862260
650 7 $aRegional planning.$2fast$0(OCoLC)fst01093120
655 0 $aElectronic books.
655 4 $aElectronic books.
700 1 $aSchintler, Laurie A.$q(Laurie Anne),$eeditor.
700 1 $aChen, Zhenhua,$eeditor.
776 08 $iPrint version:$tBig data for regional science.$dAbingdon, Oxon ; New York, NY : Routledge, an imprint of the Taylor & Francis Group, 2018$z9781138282186$w(DLC) 2017015134$w(OCoLC)975368795
830 0 $aRoutledge advances in regional economics, science and policy ;$v22.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15123678$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS