Population grid and location quotient of land cover to capture the urban-rural nature of labour market areas in Italy

Urban-rural classifications are relevant tools for the implementation of economic and social policies that put emphasis on urbanisation patterns. This paper combines a specific geography with urban-rural classifications to increase their use by policymakers. Labour market areas, long used in economic geography and regional policies, are meaningful spatial units identifying human systems based on commuting patterns. This paper develops a functional urban-rural classification which captures the relationship between human communities, their activities and the environment. The proposal identifies natural space classes, expressed through land cover, as a relevant dimension in understanding socio-economic phenomena. The proposed method classifies the communities (of people and companies) and their territories. By simultaneously defining urban and rural areas, and the territories in between, the framework leads to obvious gains in terms of comparability and harmonisation. The characterisation of communities along the urban-rural gradient is performed by means of population density, via the geometrical abstract model of grid cells. Land cover information captures the natural space characteristics and resources available in territories; the comparison with national benchmark values allows the identification of the most significant local land cover features and their distribution along urbanisation patterns. Empirical spatial entropy and sensitivity analyses investigate spatial issues. Economic validation also supports the classification's robustness. The method can be easily replicated because it uses free and open components.