Measuring Economic Activity From Space: A Case Study Using Flying Airplanes and COVID-19

This work introduces a novel solution to measure economic activity through remote sensing for a wide range of spatial areas. We hypothesize that disturbances in human behavior caused by major life-changing events leave signatures in satellite imagery that allows devising relevant image-based indicators to estimate their impact and support decision-makers. We present a case study for the COVID-19 coronavirus outbreak, which imposed severe mobility restrictions and caused worldwide disruptions, using flying airplane detection around the 30 busiest airports in Europe to quantify and analyze the lockdown's effects and postlockdown recovery. Our solution won the rapid action coronavirus earth observation (RACE) upscaling challenge, sponsored by the European Space Agency and the European Commission, and now is integrated into the RACE dashboard. This platform combines satellite data and artificial intelligence to promote a progressive and safe reopening of essential activities. Code, trained model, and data are available at https://github.com/maups/covid19-custom-script-contest.

Automated summary

This work introduces a new method to measure economic activity through remote sensing, using signatures in satellite imagery left by disturbances in human behavior to devise image indicators for estimating the impact of major life events and supporting decision-makers. A case study on the COVID-19 outbreak was presented, analyzing the effects of lockdown measures around the 30 busiest airports in Europe through airplane detection and examining post-lockdown recovery. The solution won the RACE upscaling challenge, sponsored by the European Space Agency and the European Commission, and is now integrated into the RACE dashboard, utilizing satellite data and artificial intelligence for a safe reopening of essential activities.