Mobility Patterns Assessment

Most transportation infrastructure investments build on analyses of networks and mobility patterns. Traditional mobility data such as data from mobile operators, tools based on Global Navigation Satellite System (GNSS), various infrastructure, and population maps and models, are crucial for knowledgeable decisions of authorities. However, they may not always be available, affordable, or reliable for infrastructure projects, especially in low-income countries.

Satellite imagery and analytics can play an important role in complementing traditional mobility data to empower decision-makers. Integrating EO data could provide additional mobility datasets and identify peak periods of activity, modes of transport, the presence of any physical barriers affecting the routes, movement between specific zones, and any patterns based on the origins and destinations. Intra-daily monitoring with satellite data is rather hard to attain at the moment, but the possibilities are significant in terms of observing long-term trends, peaks, and anomalies as well as understanding the greater land and urban context of infrastructure and mobility over extensive areas. Notably, most of the insights can be derived using publicly available Copernicus data, in some cases complemented by very high resolution (VHR) imagery and combined with external datasets. By integrating socio-demographic, economic and other available data with EO data, valuable insights for traffic modelling on the level of zones, cities, or even specific incidents (e.g., floods and their impact on infrastructure) are obtained.