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Sustainability 2017, 9(12), 2158; doi:10.3390/su9122158

Dynamic Land-Use Map Based on Twitter Data

1
Graduate School of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan
2
School of Management Informatics and Computer (STMIK Handayani Makassar), Makassar 90231, Indonesia
3
Department of Architecture, Faculty of Engineering, Bandar Lampung University, Bandar Lampung 35142, Indonesia
4
Department of Architecture, Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan
*
Author to whom correspondence should be addressed.
Received: 28 September 2017 / Revised: 6 November 2017 / Accepted: 17 November 2017 / Published: 23 November 2017
(This article belongs to the Section Sustainable Engineering and Science)
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Abstract

Location-based social media allows people to communicate and share information on a popular landmark. With millions of data records generated, it provides new knowledge about a city. The identification of land use intends to uncover accurate positions for future urban development planning. The purpose of this research is to investigate the use of social networking check-in data as a source of information to characterize dynamic urban land use. The data from this study were obtained from the social media application i.e., Twitter. Three kinds of data that are prioritized in this research are check-ins (specific location), timestamps, and a user’s status text or post activities. In this study, we propose a grid-based aggregation method to divide the urban area. Two different approaches are compared—rank and clustering methods to group the place’s activities. Then we utilize time distribution frequency to attain the land-use function. In this case, Makassar City, Indonesia, has been selected as the case study. An analysis shows that the check-in activity and the method we proposed can be used to group the actual land-use types. View Full-Text
Keywords: Twitter; check-in; land use; grid-based aggregation; time distribution; rank; k-means Twitter; check-in; land use; grid-based aggregation; time distribution; rank; k-means
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Yuyun; Akhmad Nuzir, F.; Julien Dewancker, B. Dynamic Land-Use Map Based on Twitter Data. Sustainability 2017, 9, 2158.

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