[COVID-19 Forum Series] 23 APR 2020 (THU) | 16:45-18:15
HKU Urban & Transport Laboratory (Room 1025, 10/F, The Jockey Club Tower) for panel members.
Registered participants to join by Zoom (Prior registration will be required. Registration is now open via the HKU Event Management System (https://hkuems1.hku.hk/hkuems/ec_hdetail.aspx?guest=Y&ueid=69541) or by sending an email to firstname.lastname@example.org. )
This forum will feature speakers showcasing and discussing the three key aspects of location intelligence, human mobility, and travel restrictions under COVID-19. A 15-minute interactive session will be scheduled at the end of the forum for participants (joining by Zoom) to exchange with panel members.
Panel Members (in alphabetical order)
PROF PC Lai Professor, Department of Geography, The University of Hong Kong
PROF Becky PY Loo Head and Professor, Department of Geography, The University of Hong Kong (Chair and Convenor)
MR Kelvin Shum Senior Director, Technology & Planning, Esri China (Hong Kong) Limited
PROF Anthony Yeh Chair Professor and Chan To-Haan Professor in Urban Planning and Design, University of Hong Kong
This is the second forum in the COVID-19 and GEOGRAPHY series initiated by HKU Geography. Transforming spatial information and data into useful knowledge has always been an essential component of geographical training. Following the discussion on converting important data from multiple sources related to SARS and COVID-19 into spatial data relevant and accessible to the general public in the first forum, this second forum begins by showcasing the technological advances in geographical information systems (GIS) that builds a common spatial data infrastructure, generates location-based insights, and supports decision-makings of all sectors in a society, especially during emergency like the COVID-19 pandemic. Human interactions are known to increase the chance of spreading infectious diseases like COVID-19. Based on the pattern of human mobility, how can GIS help to identify the high-risk hot spots and classify cities into different groups so that the most appropriate measures can be implemented to effectively curb the spatial spread of the disease? With the