EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

The potential of monitoring traffic conditions up to 15 times a day using sub-meter resolution EO images

Refiz Duro, Georg Neubauer, and Alexandra-Ioana Bojor
Refiz Duro et al.
  • AIT Austrian Institute of Technology, Center for Digital Safety and Security, Wien, Austria (

Urbanization and the trend of people moving to cities often leads to problematic traffic conditions, which can be very challenging for traffic management. It can hamper the flow of people and goods, negatively affecting businesses through delays and the inability to estimate travel times and thus plan, as well as the environment and health of population due to increased fuel consumption and subsequent air pollution. Many cities have a policy and rules to manage traffic, ranging from standard traffic lights to more dynamic and adaptable solutions involving in-road sensors or cameras to actively modify the duration of traffic lights, or even more sophisticated IoT solutions to monitor and manage the conditions on a city-wide scale. The core to these technologies and to decision making processes is the availability of reliable data on traffic conditions, and better yet real-time data. Thus, a lot of cities are still coping with the lack of good spatial and temporal data coverage, as many of these solutions are requiring not only changes to the infrastructure, but also large investments.

One approach is to exploit the current and the forthcoming advancements made available by Earth Observation (EO) satellite technologies. The biggest advantage is EOs great spatial coverage ranging from a few km² to 100 km² per image on a spatial resolution down to 0.3m, thus allowing for a quick, city-spanning data collection. Furthermore, the availability of imaging sensors covering specific bands allows the constituent information within an image to be separated and the information to be leveraged.

In this respect, we present the findings of our work on multispectral image sets collected on three occasions in 2019 using very high resolution WorldView-3 satellite. We apply a combination of machine learning and PCA methods to detect vehicles and devise their kinematic properties (e.g., movement, direction, speed), only possible with satellites with a specific design allowing for short time lags between imaging in different spectral bands. As these data basically constitute a time-series, we will discuss how the results presented fully apply to the forthcoming WorldView-Legion constellation of satellites providing up to 15 revisits per day, and thus near-real time traffic monitoring and its impact on the environment.

How to cite: Duro, R., Neubauer, G., and Bojor, A.-I.: The potential of monitoring traffic conditions up to 15 times a day using sub-meter resolution EO images, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12831,, 2021.


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