Putting back land use competition within its regional context: A typology for smart development

The previous results focused on land cover flows as indicators of land use competition dynamics. The current section put them in perspective by taking into account the overall land use shares. In this research, we indeed speculate on the stocks (of different land shares) as a resilience factor. The negative impact of land use competition is attenuated if the stock available for one weaker land use is large: in this case the adaptation capacity will be considered higher. Therefore, the new typology provides a context-ualization of the current land use dynamics within the specific regional contexts and brings indications about possible and alternatives types of development.

Clustering procedure

We conducted an Ascending Hierarchical Classification on data describing the regional land use in 2000 and the regional land use changes between 2000 and 2006 (see Ollivier et al., 2016). The analysis focuses on 639 European regions.

Regional land use competition profile

Figure 3.7 Regional land use competition profile.

Source: own treatment, data from EEA, 2015; European Union, 1995-2016 for administrative boundaries (NUTS 2/3, boundary for 2006). Using QGIS Geographic Information System, QGIS Development Team, 2016. Open Source Geospatial Foundation Project, http://qgis.osgeo.org.

from 27 countries. Eleven variables have been included, corresponding to the main land uses (artificialized land, agricultural land, forested and seminatural land) and the main land use changes (residential sprawl on agricultural land, residential sprawl on forested and semi-natural land, creation of infrastructure or economic activity sites on agricultural land, creation of infrastructure or economic activity sites on forested and semi-natural land, deforestation to create agricultural land, afforestation of agricultural land, intensification of agricultural land use, and extensification of agricultural land use). The variables have been discretized into two classes (presence/ absence) or five classes (gradient of intensity of changes), according to the variables distribution.

With the objective to acknowledge most of the structural divergences among European regional land use trajectories, a hierarchical clustering procedure has been implemented. Six groups have been created, based on inertia gain.5 This final step summarizes all the regional differences, identified by the results of the Multiple Component Analysis. The six subsequent clusters of European regions, presented on the map in Figure 3.5, reveal a regional differentiation according to some key features, which fits well with the first results obtained with the MCA method. We will present the results based on the clusters specificities for the period from 2000 to 2006, mobilizing on the data used to implement the typology.

Regional (and contextualized) land use competition typology

On that basis, we identify six main types of regions dealing with the European urban and peri-urban areas. Their main characteristics are related to the land uses and their main evolutions during the 2000-2006 period.

Agri-urban regions under deepest artificialization pressure

This first cluster is grouping 47 regions and refers to the most urbanized European rural regions, or regions with a great urban expansion. Most of these regions include a city with more than 250,000 inhabitants, like Toulouse, Leeds, Sheffield and Sofia. Others are neighbouring one, near to Paris, London, Milan, Lyon, Dublin, Rotterdam, Dusseldorf, Cologne, Copenhagen or Bucharest. This cluster includes some of the most densely populated regions of Europe,7 like regions from Netherlands, Belgium, or the French region Ile-de-France.

The regions included in this cluster are particularly urbanized: artificialized lands cover 18.6 % of the regional area in average (while the overall mean is 5.8%.) Agricultural lands are quite expanded, covering 59.2% of the regional area in average (while the overall mean is 53.3%). Forests and semi-natural lands, on the other hand, cover only 18.8% of the regional area (whereas the overall mean is 38.0%). In summary, these regions are well urbanized, cultivated but encompass rare forests and semi-naturals lands.8

In terms of land use dynamics, the cluster average of farmlands artificialized between 2000 and 2006 is twice as high as the overall mean.9 The artificialization of forests and semi-natural lands, on the other hand, can vary a lot from one region to the other, and no specific feature for the entire cluster emerges.

Agri-rural regions under time-evolving artificialization pressure

These 107 regions are predominantly agricultural, a bit urbanized and mainly contain small forests. Farmlands cover in average 80.6% of the regional area, while the forests and semi-natural lands are covering about 10% of the regional area, far below the overall mean of 38.0% of the regional area. The share of artificialized land has an average of 6.3%, which is above the overall mean (5.8% of the regional area in average). In summary, the regions of this cluster are spatially concentrated. One group lies on the coastal areas, from the south of French Brittany to the north of Denmark, including also most of the English and Irish regions. Another group is concentrated in the largest European plains: the Italian Po’ valley, the large Romanian Wallachia, the Great Hungarian plain and the Polish Central Lowlands.

In terms of land use changes, for the period 2000-2006 the main feature is an important volume of farmlands converted by the residential sprawl, the cluster average (300 hectares) being 42% above the overall mean (210 hectares) for this period. Depending of the regions, this period can be seen as a climax preceding a slower pace in urban sprawl after 2006 or, on the contrary the rising phase of a previously stifled artificialization process.10

The artificialization of farmlands due to the building of new economic sites or new transport infrastructures is also occurring in all regions, despite smaller surfaces converted in the Eastern countries than in the Western countries.

< Prev   CONTENTS   Source   Next >