XLR8| Light the Path

Light the Path

The COVID-19 pandemic initiated changes in human population movements and activities around the world. Your challenge is to use Earth observations to explore how human activity and regional land-based human movement patterns may have shifted in response to COVID-19.

Sapscience: Seeing what you may not see

Summary

The propose is the development of an app that collect data such as satellite images; graphs and histogram; tables of content, to analyze and to process the data and generate a temporal model based on the data collected, showing how the disease propagation is correlated within several subjects of a country, such as socio-economic distribution, urban infrastructure, among others. And how it affects the shift population. In addiction, the app will show which social-economics policies, chosen by the governments, were effectives to mitigate the effects of COVID-19.

How We Addressed This Challenge

The solution proposed is to collect data from many different resources (satellite images, socio-economic data-base, papers and so forth), then analyze all those information, using a machine learning technique, to integrate and connect them, in order to estimate the pattern of the virus propagation, and how it is related to the human shift and impacts on modern society. In this app, the user can get different informations of an area during the pandemic, since the main affected area, the impact on the economy, till the solutions that were able to contain the virus to spread. In the future, those data can be used to predict, avoid and to find faster solutions in cases similarities than that.

How We Developed This Project

We gathered nightlight maps, emission gas information, road map, databases related to the COVID-19 and so forth to analyze the behaviour of the population and try to identify possible issues. Then we filtered those information using image processing tools and machine learning techniques. The next step was to correlate the data to find clues that proof if the virus propagation follows a pattern related to regional aspects (infrastructure, economy, social aspects and so forth). After all, we check the effectiveness of harm reduction strategies.

We used Italy and Brazil as cases of study. Italy was chosen because was one of the first countries to suffer from the pandemic in large scale. Brazil was chosen because it didn’t reached the virus spread peak yet, and although it has a good health public program, it is facing a political divergences about what is the best measures to deal with the pandemic. However, we observed that both countries share many patterns about how the virus is spreading and this could help to create new initiatives to stop or avoid a new crisis in the future.

Finally, we propose to provide all the information on a mobile platform with public access.

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Global Judging
This project was submitted for consideration during the Space Apps Global Judging process.