This dataset describes the FRAGs (Functional Rural Area at the Grid level) and FRAUs (Functional Rural Area at the local administrative Unit level) as described in the JRC working paper Dijkstra, Jacobs-Crisioni (2023), Developing a definition of Functional Rural Areas in the EU. It also contains an overview of the matching between FRAGs and the LAU-2 units from which the FRAUs are composed.
RESOLUTION: 1:1000000.
COMPLETENESS: 100%.
POLICY CONTEXT: Regional and urban policies.
METHODOLOGY: Functional rural areas cover all the territory outside functional urban areas. They are constructed in three steps. First, we define rural centres: they are the largest town or village within a 10-minute drive. Second, we create catchment areas by assigning every grid cell to the nearby rural centre that has the greatest gravitational pull. Third, we combine small and nearby catchment areas. We combine catchment area until each has at least 25 000 inhabitants or is more than an hour’s drive away from the surrounding catchment areas. We also combine catchment areas that have centres that are less than a 30-minute drive apart, even if they have a population of at least 25 000 inhabitants. Next, we show that functional rural areas are more harmonised in terms of population and area size than LAUs and NUTS-3 regions. The analysis of population change and of the distance to the nearest school shows that the results by functional area are less volatile than the results per LAU and show more detail than the results per NUTS-3 regions. Functional rural areas can inform policies that promote access to services and that respond to demographic change. They can also be used to inform transport infrastructure investments and public transport provision.
DATA SOURCES: Settlement definitions according to degrees of urbanisation, Geostat 2011. Population based on JRC-Geostat 2018. FUAs from provisional 2021 FUA boundaries. Network connectivity and travel times from Tom Tom freeflow impedances.
LEVEL OF AGGREGATION: Functional Rural Areas
UNCERTAINTY AND LIMITATIONS: Data represent likely functionally autonomous areas, with a loose definition of functional autonomy. Not validated empirically.
European Commission, Joint Research Centre (2026): Prototype Functional Rural Areas. [Dataset] doi: 10.2905/JRC.JWE1QNR PID: http://data.europa.eu/89h/064e95ad-5a25-46d5-93eb-2344a324e2bd
Functional Rural AreasRural statisticsService provision
This dataset contains geojson files describing provisional FRAG (Functional Rural Area at the Grid level) and FRAU (Functional Rural Area at the local administrative Unit level) boundaries, as well as Excel files describing 1) the number of units in each definition, and 2) the decomposition of FRAUs into the LAU2-zones by which the FRAUs were generated.
This paper develops a methodology to define functional rural areas in the EU and seeks feedback on the method and the results. Functional rural areas are designed to cover all the territories outside functional urban areas. They are constructed in three steps. First, we define rural centres: they are the largest town or village within a 10-minute drive. Second, we create catchment areas by assigning every grid cell to the nearby rural centre that has the greatest gravitational pull. Third, we combine small and nearby catchment areas. We combine catchment area until each has at least 25,000 inhabitants or is more than an hour’s drive away from the surrounding catchment areas. We also combine catchment areas that have centres that are less than a 30-minute drive apart, even if they have a population of at least 25,000 inhabitants. Next, we show that functional rural areas are more harmonised in terms of population and area size than LAUs and NUTS-3 regions. The analysis of population change and of the distance to the nearest school shows that the results by functional area are less volatile than the results per LAU and show more detail than the results per NUTS-3 regions. Functional rural areas can inform policies that promote access to services and that respond to demographic change. They can also be used to inform transport infrastructure investments and public transport provision.
| From date | To date |
|---|---|
| 2018-01-01 | 2018-12-31 |
