This research investigates how travel restrictions affect the spatiotemporal pattern of human mobility and COVID-19 confirmed cases. Based on recorded movement and Baidu mobility index, in- and out-migration were estimated to examine the geographic pattern of human mobility across many Chinese cities from Jan 1 – Feb 11 of 2020. In addition to the baseline model of city lockdown , this study also explored the time lag effect of COVID-19 incubation period before/after Jan 28 (i.e. 5 days) and Feb 6 (i.e. 2 weeks) as well. Full factorial Analysis of Variance (ANOVA) tests reviewed significant differences of migration pattern by lockdown and origin/destination, which are also significantly associated with the confirmed cases of COVID-19 as well. Specifically, human mobility dropped proportionally after the lockdown regardless of origin location, but Hubei destination was significantly lower than non-Hubei destination. The model assuming an incubation period of 5 days differentiated the differences of COVID-19 cases better than the baseline and 14 days model. Spatiotemporal cluster analysis identified multiple space-time windows that were related to migration trajectory assuming a 5–14 days incubation period. The pre-lockdown clusters due to traveler’s outflow from Wuhan to those megacities were the pathways for international transmission of COVID-19, whereas the post-lockdown clusters were partially related to the migration pattern especially within the eastern part of Hubei around Wuhan. The geographic pattern revealed from this study confirmed the presence of super spreaders that were responsible for regional spreading at the early stage and caused local outbreaks in the latter stage.

Computers and geospatial technologies such as Geographic Information Systems, Google Earth, and the Global Positioning System (GPS) are increasingly common tools for geography instruction in schools. The NAEP Data Explorer was used to conduct an analysis of geography achievement in the eighth grade based on differences in students’ access to and uses of computers and other technologies at home and school. The analysis over the study period (1994–2018) documents the emergence of technologies available to support geography instruction. Results point to differences in geography achievement associated with differential access to technology and applications of technology for geographic learning.