A Multimodal Approach for Event Detection: Study of Uk Lockdowns in the Year 2020
2022 Ieee International Geoscience and Remote Sensing Symposium (Igarss 2022)
; : 715-718, 2022.
Article
in English
| Web of Science | ID: covidwho-2308822
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.
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Databases of international organizations
Database:
Web of Science
Language:
English
Journal:
2022 Ieee International Geoscience and Remote Sensing Symposium (Igarss 2022)
Year:
2022
Document Type:
Article
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