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Rui Xin, Linfang Ding, Bo Ai, Min Yang, Ruoxin Zhu, Bin Cao and Liqiu Meng
Bike-sharing data are an important data source to study urban mobility in the context of the coronavirus disease 2019 (COVID-19). However, studies that focus on different bike-sharing activities including both riding and rebalancing are sparse. This limi...
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Xiaogang Guo, Zhijie Xu, Jianqin Zhang, Jian Lu and Hao Zhang
Origin-destination (OD) flow pattern mining is an important research method of urban dynamics, in which OD flow clustering analysis discovers the activity patterns of urban residents and mine the coupling relationship of urban subspace and dynamic causes...
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Ran Tao, Zhaoya Gong, Qiwei Ma and Jean-Claude Thill
One of the enduring issues of spatial origin-destination (OD) flow data analysis is the computational inefficiency or even the impossibility to handle large datasets. Despite the recent advancements in high performance computing (HPC) and the ready avail...
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Tian Gan, Weifeng Li, Linghui He and Jian Li
The coronavirus disease 2019 (COVID-19) pandemic has provided an opportunity to rethink the development of a sustainable and resilient city. A framework for comprehensive intracity pandemic risk evaluation using mobile phone data is proposed in this stud...
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Zhenzhou Xu, Ge Cui, Ming Zhong and Xin Wang
Anomalous urban mobility pattern refers to abnormal human mobility flow in a city. Anomalous urban mobility pattern detection is important in the study of urban mobility. In this paper, a framework is proposed to identify anomalous urban mobility pattern...
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