Collection of Open Source GIS project work during Spring 2021
This blog post is a reflection on the work presented by Dr. Mei-Po Kwan of the Chinese University of Hong Kong for the American Geographical Society on 9 September, 2020, discussing the efficiency and implications of Tracking Movement through Space during COVID-19and Beyond.
For this reflection, I was assigned to support the expansion of capabilities and applications of spatial big data research. Therefore, the arguments put forth in the following reflection do not accurately represent my personal opinion on the matter; however, there are effective arguments for the expansion and curtailing of these capabilities, and context plays a significant role in the ability of such data to be applied responsibly and effectively.
Dr. Mei-Po Kwan is a Professor of Geography and Resource Management at the Chinese University of Hong Kong, and therefore has spent a good deal of time studying how geospatial analysis in GIS systems can contribute to helping aid vulnerable populations all over the world. As an example, Dr. Kwan spotlighted the plight of sex workers in Mexico - US border cities, who are hesitant or unwilling to travel to certain areas of their urban environments for fear of harassment or exploitation by police forces. Dr. Kwan was able to actually map their “geospatial narratives” and color-code, to a building-level scale, where this vulnerable population would and would not move.
Dr. Kwan raised an important counterpoint during her presentation, as well. Contributing to these geospatial narratives requires state-of-the-art (and very accurate) tracking technology, which can often be devoid of social and geospatial context. This dimensionless data can then unintentionally disclose too much about vulnerable populations, especially when it comes to health data, and cause more harm than good. This issue has come under particular scrutiny as governments across the world scramble to track and contain COVID-19, with many resorting to temporary contact tracing and tracking procedures to keep a handle on the spread of the virus.
While there are some negative aspects of this tracking, there are nevertheless tried and tested ways to conduct accurate tracking properly and respectfully. Dr. Kwan finishes her talk with a mention of new Bluetooth-based tracking technologies and academic-led data sharing enclaves, which may help preserve privacy of individuals while still providing authorities with an accurate illustration of the movement of COVID-19 through their communities. Bluetooth only tells a user who is around them, and only if those individuals actively share that information. These solutions could be the perfect balance of developing a better understanding of human space-time behavior through big data while still respecting the privacy and humanism of individuals providing that data. Even if these technologies are not perfected yet, they have the potential to be refined and updated over time and more and more geospatial scientists start paying attention to these important questions and data sources, and edit existing methodologies to further preserve social and geographic context in big data sources in order to provide the most respectful and accurate illustration of human populations possible.
References:
“Tracking Movement through Space during COVID-19 and Beyond” - Dr. Mei-Po Kwan speaking for the American Geographical Society, 9 September 2020
Submitted 9 May 2021