- Titel:
Explaining demand patterns during COVID-19 using opportunistic data: a case study of the city of Munich
- Dokumenttyp:
- Zeitschriftenaufsatz
- Autor(en):
- Mahajan, Vishal ; Cantelmo, Guido ; Antoniou, Constantinos
- Stichworte:
- Original Paper ; Transport in the COVID-19 Virus Era ; COVID-19 ; Demand patterns ; POIs ; Spatial-temporal ; Crowdsensed data ; Machine learning
- Zeitschriftentitel:
- European Transport Research Review
- Jahr:
- 2021
- Band / Volume:
- 13
- Heft / Issue:
- 1
- Volltext / DOI:
- doi:10.1186/s12544-021-00485-3
- Verlag / Institution:
- Springer International Publishing
- E-ISSN:
- 1867-0717 ; 1866-8887
- Hinweise:
- 0
- Publikationsdatum:
- 12.04.2021
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