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Geo-spatial Information Science Volume 19, 2016 - Issue 2: Big Data in Geo-spatial Information Science
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Articles

Latent spatio-temporal activity structures: a new approach to inferring intra-urban functional regions via social media check-in data

Ye ZhiRoad Traffic Safety Research Center of the Ministry of Public Security, Beijing, China
,
Haifeng LiSchool of Geosciences and Info-Physics, Central South University, Changsha, China
,
Dashan WangRoad Traffic Safety Research Center of the Ministry of Public Security, Beijing, China
,
Min DengSchool of Geosciences and Info-Physics, Central South University, Changsha, China
,
Shaowen WangCyberGIS Center for Advance Digital and Spatial Studies, University of Illinois at Urbana-Champaign, Urbana, IL, USA
,
Jing GaoCyberGIS Center for Advance Digital and Spatial Studies, University of Illinois at Urbana-Champaign, Urbana, IL, USA
,
Zhengyu DuanKey Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai, China
&
Yu LiuInstitute of Remote Sensing and Geographical Information Systems, Peking University, Beijing, ChinaCorrespondence[email protected]
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Pages 94-105 | Received 12 Jan 2016, Accepted 29 Feb 2016, Published online: 17 May 2016

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Qingfeng Guan, Jianfeng Zhou, Ruifan Wang, Yao Yao, Chen Qian, Yaqian Zhai & Shuliang Ren. (2022) Understanding China’s urban functional patterns at the county scale by using time-series social media data. Journal of Spatial Science 0:0, pages 1-19.
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Lun Wu, Ximeng Cheng, Chaogui Kang, Di Zhu, Zhou Huang & Yu Liu. (2020) A framework for mixed-use decomposition based on temporal activity signatures extracted from big geo-data. International Journal of Digital Earth 13:6, pages 708-726.
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Yong Gao, Jing Cheng, Haohan Meng & Yu Liu. (2019) Measuring spatio-temporal autocorrelation in time series data of collective human mobility. Geo-spatial Information Science 22:3, pages 166-173.
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Wei Huang & Songnian Li. (2019) An approach for understanding human activity patterns with the motivations behind. International Journal of Geographical Information Science 33:2, pages 385-407.
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