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International Geoscience and Remote Sensing Symposium

In 2021 a joint initiative of Belgium and The Netherlands

FR1.O-19.6

DETECTING AIRPORT ACTIVITY FROM SENTINEL-2 IMAGERY DURING COVID-19 PANDEMIC BY USING DEEP LEARNING

Hang Yang, University of Tokyo, Japan; Toru Kouyama, Fumiharu Suzuki, National Institute of Advanced Industrial Science and Technology, Japan; Shutaro Sato, Ichiro Yoshikawa, University of Tokyo, Japan
Session:
Monitoring the Impacts of COVID from Space
Track:
Special Themes
Presentation Time:
Fri, 16 Jul, 09:45-10:00 (UTC)
Fri, 16 Jul, 11:45-12:00 Central Europe Summer Time (UTC +2)
Fri, 16 Jul, 17:45-18:00 China Standard Time (UTC +8)
Fri, 16 Jul, 05:45-06:00 Eastern Daylight Time (UTC -4)
Session Co-Chairs:
Ruyi Feng, China University of Geosciences(Wuhan) and Linus Scheibenreif, University of St. Gallen
Session Manager:
Lydia Abady
Presentation
Discussion
Resources
Session FR1.O-19
FR1.O-19.1: IMPACT OF RESTRICTION DUE TO COVID-19 ON AIR POLLUTION IN POLAND IN SPIRING 2020
Patryk Tadeusz Grzybowski, Krzysztof Markowicz, University of Warsaw, Poland; Jan Paweł Musiał, Institute of Geodesy and Cartography, Poland
FR1.O-19.2: A NOVEL DATASET AND BENCHMARK FOR SURFACE NO2 PREDICTION FROM REMOTE SENSING DATA INCLUDING COVID LOCKDOWN MEASURES
Linus Scheibenreif, Michael Mommert, Damian Borth, University of St. Gallen, Switzerland
FR1.O-19.3: AIR QUALITY IMPROVEMENT DURING COVID-19 PANDEMIC: STUDY OF LAND AND MARITIME POLLUTION
Pedro Silva, Mariana Ávila, Emanuel Castanho, Atlantic International Research Centre, Portugal
FR1.O-19.4: IMPACT OF COVID19-INDUCED LOCKDOWN ON AIR QUALITY IN IRELAND
Dewansh Kaloni, The ADAPT Centre, Ireland; Yee Hui Lee, Nanyang Technological University, Singapore; Soumyabrata Dev, University College Dublin, Ireland
FR1.O-19.5: AN ANALYSIS FOR THE WORK RESUMPTION UNDER THE COVID-19 EPIDEMIC BASED ON VIIRS-DNB NIGHTTIME LIGHTS IN CHINA
Suzheng Tian, Ruyi Feng, Lizhe Wang, China University of Geosciences, China
FR1.O-19.6: DETECTING AIRPORT ACTIVITY FROM SENTINEL-2 IMAGERY DURING COVID-19 PANDEMIC BY USING DEEP LEARNING
Hang Yang, University of Tokyo, Japan; Toru Kouyama, Fumiharu Suzuki, National Institute of Advanced Industrial Science and Technology, Japan; Shutaro Sato, Ichiro Yoshikawa, University of Tokyo, Japan

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