City typology

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Urban Green Infrastructure (GI) typology and its analysis are expected to feed into urban sustainability by providing insights on the environmental performance of cities with regard to urban GI. Accordingly, a cluster analysis has been performed to identify cities that have similar characteristics when it comes to certain urban green infrastructure elements.

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The clustering of the cities has been based on nine parameters: share of green urban areas (GUAs), degree of soil sealing, distribution of GUAs, effective GI (urban hinterland), hotspot ratio (hinterland), terrestrial urban blue areas, low density areas, share of urban forest and share of Natura 2000 sites.

Table 1. Description of the parameters used to determine the Green Infrastructure typology

Share of GUAs	This parameter is based on several classes (11230, 11240, 14100, 14200, 20000, 30000) of the Urban Atlas data, which contain substantial green spaces (the two least dense residential classes with a sealing degree < 30 %, urban parks, sports and leisure facilities, forest, semi-natural and agriculture). It is computed for the core city as defined by Eurostat/Urban Audit. Dataset: Urban Atlas 2006 (resolution 0,25ha). Reference unit: core city.
Degree of soil sealing	The degree of the sealed surfaces in cities Dataset: High Resolution Layer Imperviousness (2009), (resolution 20 m). Reference unit: core city.
Distribution of GUAs	Approximation of the distribution of GUAs by measuring the edges between the green and non-green areas and computing the edge density. The edge lengths are given in relation to a one-hectare cell (m/ha). Dataset: Urban Atlas 2006 (resolution 0.25 ha for urban classes and 1 ha for non-urban classes). Reference unit: core city.
Effective GI (urban hinterland)	The mean effective GI is based on fifty 1 km circular zones around the city centre point (minus the core city). The final value represents the average of GI patches inside all circular zones. For the smallest cities these zones often go beyond the spatial boundary of the Urban Atlas cities. Dataset: Corine Land Cover 2006 (resolution 25 ha). Reference unit: 50 km circle around the city.
Hotspot ratio (hinterland)	The hotspot ratio is defined as those areas where a high GI potential and a considerable urban effect coincide. It is also based on the buffer circular zones around the city centre. The final value is the average of all circular zones. Dataset: Corine Land Cover 2006 (resolution 25 ha). Reference unit: 50 km circle around the city.
Terrestrial urban blue areas	Share of blue areas within cities. Sea areas are not included as they are mostly outside the official city boundary and, therefore, are not covered by the Urban Atlas. Dataset: Urban Atlas 2006 (Water class: 50000) Reference unit: core City
Low density areas	Provides an indication of the share of residential areas with a low population density (low sealing degree). These areas with small green spaces, generally private gardens, typically represent sprawling cities. Dataset: Urban Atlas 2006 (classes: 11220, 11230, 11240, 11300, and 12400). Reference unit: core City
Share of urban forest	Proportion of forests within cities. This is a sub-indicator of the share of GUAs, which indicates whether or not the green spaces contain lots of forest. Dataset: Urban Atlas 2006 Reference unit: core City
Share of Natura 2000 sites	Proportion of Natura 2000 sites within cities. Dataset: Natura 2000 sites database Reference unit: core City

Main characteristics of clusters

Once the clusters have been identified, both the centroid of each cluster and the distance of each parameter to the centroid were calculated in order to highlight the main characteristics defining each group. Here, the centroid is the mean value of all indicators for those cities that fall within the cluster. Those parameters that show larger distances are the ones that make the difference and characterise the group.

From this process, eight clusters emerged that can be defined by their main characteristics as ‘Fragmented cities’, ‘Green outskirts cities’, ‘Natural cities’, ‘Hotspot cities’, ‘Green cities’, ‘Green-grey sealed cities’, ‘Forest cities’, and ‘Natural blue cities’.

Table 2. Description of clusters by main characteristics [Still to be edited]

Cluster	Name	Main characteristics	N of cities
1	Fragmented cities	Medium values of low-density residential fabric (also the parameter with the greatest distance to the cluster centre) Medium values of the distribution of green urban areas Low to medium values of the proportion of green urban areas and degree of soil sealing	49
2	Green outskirts cities	High values of effective green infrastructure (also the parameter with the highest distance to the cluster centre) High proportions of green urban areas Medium to high distribution of green urban areas Medium degree of soil sealing	42
3	Natural cities	Very high proportion of green urban areas Very high proportion of Natura 2000 sites (the parameter with the greatest distance to the cluster centre) Very high shares of effective green infrastructure Medium proportion of urban forests and very low degree of soil sealing	9
4	Hotspot cities	Very high hotspot ratio (also also by far the parameter with the greatest distance to the cluster centre) High soil sealing degrees and low shares of green urban areas	3
5	Green cities	Very high share of green urban areas and a correspondingly low degree of soil sealing (their significance, i.e. the distance to the cluster centre, is almost equal) Medium to high effective green infrastructure	113
6	Green-grey sealed cities	High degree of soil sealing and low proportion of green urban areas (which are relatively well distributed) Low proportion of urban forests Relatively low amount of effective green infrastructure, Natura 2000 sites and low density areas	85
7	Forest cities	High proportion of urban forests (also the parameter with the greatest distance to the cluster centre) High to very high proportion of green urban areas and effective green infrastructure Low share of low density residential areas, low soil sealing degrees	73
8	Natural blue cities	High proportion of urban blue areas (also the parameter with the greatest distance to the cluster centre) High proportion of Natura 2000 areas Medium to high proportion of effective green infrastructure Medium to high proportion of green urban areas	11

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Austria Belgium Bulgaria Croatia Cyprus Czechia Denmark Estonia Finland France Germany Greece Hungary Iceland Ireland Italy Latvia Liechtenstein Lithuania Luxembourg Malta Netherlands Norway Poland Portugal Romania Slovakia Slovenia Spain Sweden Switzerland Turkey United Kingdom

For references, please go to https://eea.europa.eu./themes/sustainability-transitions/urban-environment/urban-green-infrastructure/typology-for-urban-green-infrastructure or scan the QR code.

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