A Multimodal Approach for Event Detection: Study of UK Lockdowns in the Year 2020.

Item Type	Conference or Workshop Item (Paper)
Abstract	Satellites allow spatially precise monitoring of the Earth, but provide only limited information on events of societal impact. Subjective societal impact, however, may be quantified at a high frequency by monitoring social media data. In this work, we propose a multi-modal data fusion framework to accurately identify periods of COVID-19-related lockdown in the United Kingdom using satellite observations (NO2 measurements from Sentinel-5P) and social media (textual content of tweets from Twitter) data. We show that the data fusion of the two modalities improves the event detection accuracy on a national level and for large cities such as London.
Authors	Hanna, Joëlle; Scheibenreif, Linus Mathias; Mommert, Michael & Borth, Damian
Research Team	AIML Lab
Language	English
Subjects	computer science
HSG Classification	contribution to scientific community
Date	19 July 2022
Publisher	IEEE Geoscience and Remote Sensing Society
Number of Pages	4
Event Title	IEEE Geoscience and Remote Sensing Symposium 2022
Event Location	Kuala Lumpur, Malaysia
Event Dates	17-22 July 2022
Official URL	https://igarss2022.org/view_paper.php?PaperNum=338...
Contact Email Address	joelle.hanna@unisg.ch
Depositing User	Joëlle Hanna
Date Deposited	14 Sep 2022 07:57
Last Modified	28 Sep 2022 09:19
URI:	https://www.alexandria.unisg.ch/publications/267271

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Hanna, Joëlle; Scheibenreif, Linus Mathias; Mommert, Michael & Borth, Damian: A Multimodal Approach for Event Detection: Study of UK Lockdowns in the Year 2020. 2022. - IEEE Geoscience and Remote Sensing Symposium 2022. - Kuala Lumpur, Malaysia.

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https://www.alexandria.unisg.ch/id/eprint/267271

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