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Geographic space as a living structure for predicting human activities using big data
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.ORCID iD: 0000-0002-2337-2486
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
2018 (English)In: International Journal of Geographical Information Science, ISSN 1365-8816, E-ISSN 1365-8824Article in journal (Refereed) Epub ahead of print
Abstract [en]

Inspired by Christopher Alexander's conception of the world - space is not lifeless or neutral, but a living structure involving far more small things than large ones - a topological representation has been previously developed to characterize the living structure or the wholeness of geographic space. This paper further develops the topological representation and living structure for predicting human activities in geographic space. Based on millions of street nodes of the United Kingdom extracted from OpenStreetMap, we established living structures at different levels of scale in a nested manner. We found that tweet locations at different levels of scale, such as country and city, can be well predicted by the underlying living structure. The high predictability demonstrates that the living structure and the topological representation are efficient and effective for better understanding geographic forms. Based on this major finding, we argue that the topological representation is a truly multiscale representation, and point out that existing geographic representations are essentially single scale, so they bear many scale problems such as modifiable areal unit problem, the conundrum of length and the ecological fallacy. We further discuss on why the living structure is an efficient and effective instrument for structuring geospatial big data, and why Alexander's organic worldview constitutes the third view of space.

Place, publisher, year, edition, pages
Taylor & Francis , 2018.
Keywords [en]
Organic worldview, topological representation, tweet locations, natural cities, scaling of geographic space
National Category
Social and Economic Geography
Identifiers
URN: urn:nbn:se:hig:diva-26177DOI: 10.1080/13658816.2018.1427754OAI: oai:DiVA.org:hig-26177DiVA, id: diva2:1184735
Available from: 2018-02-22 Created: 2018-02-22 Last updated: 2018-03-13Bibliographically approved

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Jiang, BinRen, Zheng

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CiteExportLink to record
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  • apa
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  • ieee
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  • sv-SE
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