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Visualization of the Epidemic Situation of COVID-19
Journal of Geo-Information Science ; 23(2):211-221, 2021.
Article in Chinese | Scopus | ID: covidwho-1639336
ABSTRACT
The COVID-19 epidemic has extremely attracted our attentions and lots of maps and visualization charts were created to represent and disseminate the information about COVID-19 in time, which exactly became a key role for the public to acquire and understand the quantitative information and spatial-temporal information of COVID-19. The paper analyzed the dimension of data for COVID-19 and processing levels about them, then divided the COVID-19 visualization into three types, that is 1-order visualization, 2-order visualization and multi-order visualization for COVID-19, based on direct data or indirect data of COVID-19 with the corresponding visualization methods, characteristics and information transmission Shortcomings and weakness of visualization methods for COVID-19 were analyzed in details, from the aspects of multiple scale unit in spatial data statistics, max value dealing in data classification, also many key design points were described including color connotation in disease visualization, the influences of area / unit size in visualization, symbol overlapping, multiple-scale heat maps and labels in statistical tables. The paper indicated the visualization traps of COVID-19, such as misuse of visual effects and excessive visualization, and reasonable abilities of COVID-19 visualization including map-story narrative methods and visualization pertinence for specific problems should be considered sufficiently to provide the references for cartographers to design the maps and for readers to understand the maps. 2021, Science Press. All right reserved.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: Chinese Journal: Journal of Geo-Information Science Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: Chinese Journal: Journal of Geo-Information Science Year: 2021 Document Type: Article