Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic

Exploration of dynamic human activity gives significant insights into understanding the urban environment and can help to reinforce scientific urban management strategies. Lots of studies are arising regarding the significant human activity changes in global metropolises and regions affected by COVI...

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Veröffentlicht in:	PloS one 2023-01, Vol.18 (1), p.e0277913-e0277913
Hauptverfasser:	Chen, Tongxin, Zhu, Di, Cheng, Tao, Gao, Xiaowei, Chen, Huanfa
Format:	Artikel
Sprache:	eng
Schlagworte:	Activity patterns Algorithms Analysis Big Data Case studies Cellular telephones Censuses Cities Clustering Communicable Disease Control Control Coronaviruses COVID-19 COVID-19 - epidemiology Datasets Disease transmission Earth Sciences Engineering and Technology Epidemics Evaluation Geospatial data Health behavior Heat affected zone Homogeneity Human Activities Humans Land use London - epidemiology Machine learning Medicine and Health Sciences Mobility Pandemics Phases Policies Research and Analysis Methods Resource allocation Social Sciences Statistical analysis Urban areas Urban environments Variation
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