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Title:

Explaining demand patterns during COVID-19 using opportunistic data: a case study of the city of Munich

Document type:
Zeitschriftenaufsatz
Author(s):
Mahajan, Vishal ; Cantelmo, Guido ; Antoniou, Constantinos
Keywords:
Original Paper ; Transport in the COVID-19 Virus Era ; COVID-19 ; Demand patterns ; POIs ; Spatial-temporal ; Crowdsensed data ; Machine learning
Journal title:
European Transport Research Review
Year:
2021
Journal volume:
13
Journal issue:
1
Fulltext / DOI:
doi:10.1186/s12544-021-00485-3
Publisher:
Springer International Publishing
E-ISSN:
1867-0717 ; 1866-8887
Notes:
0
Date of publication:
12.04.2021
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