Abstract
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.
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Data and Code availability
The input datasets are publicly available and referenced in the text. The datasets generated during the current study are available from the corresponding author on reasonable request. The microdata used in the validation step are available at the Italian National Statistical Institute under the framework of access for scientific research purposes. The code is available from the authors.
Notes
Currently, at the EU level, NUTS3 regions (EU Nomenclature of Territorial Units for Statistics) are the smallest aggregations of municipalities having a proper urban-rural classification. In Italy, out of 107 NUTS3 regions, 52 per cent are intermediate, 28 per cent are urban and 20 per cent are rural.
Since the 1990s, LMAs represent an alternative geography for public policies in Italy —e.g. they identify areas affected by industrial crises (Bellandi et al., 2020).
Self-contained labour areas in Canada: https://www150.statcan.gc.ca/n1/daily-quotidien/230210/dq230210c-eng.htm; Travel-To-Work-Areas in the UK: https://geoportal.statistics.gov.uk/datasets/travel-to-work-areas-2011-guidance-and-information/about; labour market areas in Switzerland: https://www.bfs.admin.ch/bfs/en/home/news/whats-new.gnpdetail.2019-0439.html.
At the EU level, the Geostat 2011 population grid 1 K is available at https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/population-distribution-demography/geostat. Worldwide, see Schiavina et al. (2022) http://data.europa.eu/89h/d6d86a90-4351-4508-99c1-cb074b022c4a.
Percentages refer to Italy.
Settlements with more than 100 resident employees and showing in-flow commuting greater than out-flow. Data available at: https://www.istat.it/it/informazioni-territoriali-e-cartografiche/sistemi-locali-del-lavoro/indicatori-di-qualit%C3%A0-sll
2018 figures.
The ageing index is the ratio of the population aged 65 and over to the young population (aged 0–14); the total age dependency ratio represents the number of individuals who are likely to be ‘dependent’ on the support of others for their daily living—the young and the elderly—in comparison to the number of those individuals who are capable of providing this support.
Over the years, tourism in Italy has changed its structure, following global sustainability trends. Nature-related activities, agriculture and rural lifestyles gathered an increasingly important role in the supply of tourist services. Consequently, rural tourism, as defined by UNWTO, contributes to the growth/wealth of local economies. https://www.unwto.org/world-tourism-day-2020/tourism-and-rural-development-technical-note; https://www.unwto.org/rural-tourism
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This work has been developed under Istat programme for thematic research projects and has partially been funded by Eurostat Grant Agreement N. 882021 2019-IT-Subnational and by PON GOVERNANCE 2014-2020 Informazione statistica territoriale e settoriale per le politiche di coesione 2014-2020. Istat is not responsible for any view expressed in this paper.
The authors would like to thank the referee for valuable comments which helped to improve the manuscript.
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Partial financial support was received from: Eurostat Grant Agreement N. 882021 2019-IT-Subnational and PON GOVERNANCE 2014–2020 Informazione statistica territoriale e settoriale per le politiche di coesione 2014–2020.
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Luisa Franconi, Marianna Mantuano and Daniela Ichim are responsible for: Conceptualization, Methodology, Software, Data curation, Visualization, Investigation, Analysis, Validation, Writing and Editing.
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Franconi, L., Mantuano, M. & Ichim, D. Population grid and location quotient of land cover to capture the urban-rural nature of labour market areas in Italy. GeoJournal 89, 6 (2024). https://doi.org/10.1007/s10708-024-11000-1
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DOI: https://doi.org/10.1007/s10708-024-11000-1