Urbanisation of rural areas: A case study from Jutland, Denmark

TLDR

Urbanisation, a key driver of spatial development in Europe, involves both land‑use and socio‑economic changes, and analysing it along an urban‑rural continuum with diverse indicators is particularly relevant in Denmark after the 2007 administrative reform. The study examines whether parish‑level socio‑economic data can refine urban‑rural classifications in Region Midtjylland, Denmark. The authors aggregated parish‑level socio‑economic data and applied multivariate and GIS analyses to identify and map five distinct urbanisation types. The analysis revealed that rural areas in Region Midtjylland are highly diverse, largely aligning with the 2006 Danish National Planning Report, yet the finer‑grained, indicator‑based approach offers a more detailed classification.

Abstract

Abstract Geografisk Tidsskrift—Danish Journal of Geography 110(1):47–63, 2010 The growth of urban areas is one of the most important characteristics of spatial development in Europe during the past decades and is traditionally described with a few indicators on a relatively coarse spatial scale. However, urbanisation is not only a matter of land use change, but also socio-economic changes, which may or may not manifest itself as physical changes in built-up area and land use. It is therefore useful to analyse the urbanisation patterns along an urban-rural continuum, based on a broad range of indicators. This paper analyses urbanisation patterns in rural areas of Region Midtjylland, Denmark using socio-economic data from the entire rural population aggregated at parish level to investigate if this method may contribute to existing classifications. Through multivariate analysis and GIS analysis, five types of urbanization were identified and their spatial distribution analysed. The results indicate that rural areas of Region Midtjylland are very diverse, and generally reflect the pattern described in the 2006 Danish National Planning Report. However, our results offer a more fine-grained analysis based on scientifically selected indicators which is an important step to improve existing classifications. This is especially relevant in a Danish context following the administrative reform in 2007 which renders the traditional classifications less suited for locally adapted planning and policy formulation.