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Representation and analytical models for location-based big data
Department of Geography, University of Georgia, Athens, USA.ORCID iD: 0000-0003-2719-2017
Department of Geography, Universitat Zurich Institut fur Geographie, Zurich, Switzerland.ORCID iD: 0000-0001-8399-3607
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Geospatial Sciences.ORCID iD: 0000-0002-2337-2486
University of Augsburg, Augsburg, Germany.
2019 (English)In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824, Vol. 33, no 4, p. 707-713Article in journal, Editorial material (Refereed) Published
Place, publisher, year, edition, pages
Taylor & Francis , 2019. Vol. 33, no 4, p. 707-713
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Physical Geography Civil Engineering
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URN: urn:nbn:se:hig:diva-29190DOI: 10.1080/13658816.2018.1562068ISI: 000459561600004Scopus ID: 2-s2.0-85059679355OAI: oai:DiVA.org:hig-29190DiVA, id: diva2:1283252
Available from: 2019-01-28 Created: 2019-01-28 Last updated: 2019-11-29Bibliographically approved

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Jiang, Bin

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