  In order to mitigate the spread of COVID-19, Wuhan was the first city to
implement strict lockdown policy in 2020. Even though numerous researches have
discussed the travel restriction between cities and provinces, few studies
focus on the effect of transportation control inside the city due to the lack
of the measurement and available data in Wuhan. Since the public transports
have been shut down in the beginning of city lockdown, the change of traffic
density is a good indicator to reflect the intracity population flow.
Therefore, in this paper, we collected time-series high-resolution remote
sensing images with the resolution of 1m acquired before, during and after
Wuhan lockdown by GF-2 satellite. Vehicles on the road were extracted and
counted for the statistics of traffic density to reflect the changes of human
transmissions in the whole period of Wuhan lockdown. Open Street Map was used
to obtain observation road surfaces, and a vehicle detection method combing
morphology filter and deep learning was utilized to extract vehicles with the
accuracy of 62.56%. According to the experimental results, the traffic density
of Wuhan dropped with the percentage higher than 80%, and even higher than 90%
on main roads during city lockdown; after lockdown lift, the traffic density
recovered to the normal rate. Traffic density distributions also show the
obvious reduction and increase throughout the whole study area. The significant
reduction and recovery of traffic density indicates that the lockdown policy in
Wuhan show effectiveness in controlling human transmission inside the city, and
the city returned to normal after lockdown lift.
