  This work introduces a novel solution to measure economic activity through
remote sensing for a wide range of spatial areas. We hypothesized 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 impacts 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 post-lockdown 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 integrates the RACE
dashboard. This platform combines satellite data and artificial intelligence to
promote a progressive and safe reopening of essential activities. Code and CNN
models are available at https://github.com/maups/covid19-custom-script-contest
