As a joint effort by scholars and professionals from the Center for Geographical Analysis at Harvard University, the Geo-Computation Center for Social Sciences at Wuhan University, the China Data Institute, the RMDS Lab, and some other institutions, a new initiative of “Global Research on COVID-19” was launched on January 2020, which aims to provide an information infrastructure for the spatial study of the new novel coronavirus (COVID-19). The objectives of this project are: (1) to provide data support for the spatial study of COVID-19 at local, regional and global levels; (2) to facilitate quantitative research on spatial spreading and impacts of COVID-19 with advanced methodology and technology; (3) to promote collaborative research on the spatial study of COVID-19; and (4) to build research capacity for future collaborative projects.
This webinar series is a core component of this initiative. Topics include:
1. COVID-19 Data Collection and Integration. Xinyan Zhu and Yuanzheng Shao, Wuhan University
2. Understanding the COVID-19 Data. Shuming Bao, China Data Institute
3. COVID-19 Data Analysis with Workflows. Tao Hu, Harvard University
4. Spatial Analysis and Visualization of COVID-19 Data. Wendy Guan, Harvard University; Pinde Fu, ESRI
5. Spatial-temporal Analysis on COVID-19 Data. Chaowei Yang, George Mason University
6. A Spatiotemporal Projection of the County-level COVID-19 Risk in the USA. Peter Song, University of Michigan
7. Workflow-based Spatial Statistical Analysis on COVID-19 Data. Lingbo Liu, Wuhan University
8. The Correlation Analysis of Mobility Network and Coronavirus Diffusion. Kun Qin, Wuhan University
9. The Impact Analysis of Coronavirus on Regional Economics with Panel Data. Yumin Wu, East China University of Sciences and Technology
This webinar will be presented in Chinese. The English webinars will be announced later. You will receive a confirmation email with the instruction for joining the webinar once you have registered online. For further information please contact spatialdatalab@lists.fas.harvard.edu.
LOCATION: STATUS:CONFIRMED DTSTART:20200501T010000Z DTEND:20200501T020000Z END:VEVENT END:VCALENDAR