Territorial typologies manual - cluster types


This article forms part of Eurostat’s methodology manual on territorial typologies.

Cluster types are groups of 1 km² population grid cells that share similar characteristics, based on a combination of their population density and geographical contiguity.

Full article

Classes for the typology and their conditions

Details of the typology

The following three types of clusters may be identified:

  • urban centre (high-density cluster): a cluster of contiguous grid cells of 1 km² (excluding diagonals) with a population density of at least 1 500 inhabitants per km² and collectively a minimum population of 50 000 inhabitants after gap-filling;
  • urban cluster (moderate-density cluster): a cluster of contiguous grid cells of 1 km² (including diagonals) with a population density of at least 300 inhabitants per km² and a minimum population of 5 000 inhabitants;
  • rural grid cells: grid cells that are not identified as urban centres or as urban clusters.

Methodology for the typology

Cluster types may be identified in relation to the total population living in 1 km² grid cells; note, the introductory chapter provides a more detailed explanation of the population grid. The vast majority of the geographical territory of the European Union (EU) (continental Europe, the Açores, Canarias and Madeira) is covered by the GEOSTAT population grid, while the remaining outermost regions are covered by a global population grid produced by the Joint Research Centre (JRC) of the European Commission.

Each cluster type is identified by classifying 1 km² population grid cells according to characteristics that are based on their total population and population density. Grid cells are classified according to the steps detailed below (note that a cell may belong to an urban centre and an urban cluster as their definitions are not mutually exclusive).

Understanding contiguous cells

Before looking at the identification of the three cluster types, it is necessary to understand the concept of contiguous cells. Figure 1 shows an array of nine grid cells, with the focus on the central cell which is surrounded by eight others, numbered 1 to 8.

Figure 1: Contiguous grid cells

Two types of contiguous grid cells can be identified:

  • a narrower definition excluding diagonals: all cells that touch each other excluding those cells that only touch each other on a diagonal; only cells numbered 2, 4, 5 and 7 are contiguous to the central cell in Figure 1 according to this narrower definition, which is used for identifying urban centres (high-density clusters).
  • a broad definition including diagonals: all cells that touch each other in any way, including cells that are linked only on a diagonal; all cells numbered 1 to 8 are contiguous to the central cell in Figure 1 according to this broader definition, which is used for identifying urban (moderate-density) clusters.

Step 1: identifying urban centres (high-density clusters)

The identification of urban centres (high-density clusters) is done in two steps: first, all cells with a population density of at least 1 500 inhabitants per km² are plotted (light blue shading in Figure 2); secondly, groups of contiguous grid cells are identified (groups G1 and G2 in Figure 2); remember that these contiguous grid cells may include cells that are linked only on a diagonal — as shown, for example, by cell C2.

The method used to identify urban centres (high-density clusters) is similar to that used for urban (moderate-density) clusters. Rather than using a threshold of 300 inhabitants per km², the identification of urban centres is based on grid cells with a population density of at least 1 500 inhabitants per km² (see Figure 2).

Contiguous cells are grouped together: however, when identifying urban centres diagonal contiguity is excluded. As such, in the example of Figure 2, cells C2 and D3 are not considered as contiguous; rather, they are each part of different groups (G1 and G2).

Figure 2: Contiguous groups for urban centres

In a second step, each group of contiguous grid cells is analysed in relation to its total number of inhabitants and only those groups of contiguous cells with 50 000 inhabitants or more are selected (see Figure 3).

Figure 3: Identifying urban centres

The identification of urban centres involves a third step, which is taken to fill gaps and smooth borders. This is done by applying an iterative majority rule: if five or more of the (eight) cells surrounding a particular cell belong to the same unique urban centre, then that cell is also considered to belong to the same urban centre; this process is repeated (iteratively) until no more cells are added. Note that the criterion for gap-filling includes cells that are linked only on a diagonal. For example, cell B2 on the left-hand side of Figure 3 has seven of its eight surrounding cells that belong to the same urban centre. This cell should therefore subsequently be added to the urban centre to smooth borders (as shown on the right-hand side of Figure 3).

Step 2: identifying urban clusters (moderate-density clusters)

The method used to identify urban clusters (moderate-density clusters) is similar to that used for urban centres (high-density clusters). Rather than using a threshold of at least 1 500 inhabitants per km², the identification of urban clusters is based on grid cells with a population density of at least 300 inhabitants per km² (see Figure 4).

Figure 4: Contiguous groups for urban clusters

The identification of urban clusters is done in two steps: first, all cells with a population density of at least 300 inhabitants per km² are plotted (light blue shading in Figure 4); secondly, groups of contiguous grid cells are identified (groups G1 and G2 in Figure 4); note that contiguous grid cells may include cells that are linked only on a diagonal — as shown, for example, by cell C2.

Figure 5: Identifying urban clusters

Thereafter, each group of contiguous grid cells is analysed in relation to its number of inhabitants and those groups of contiguous cells with 5 000 inhabitants or more are selected; these are urban clusters. Continuing with the same example, Group G1 is considered an urban cluster as it has a population of 7 000 inhabitants, as shown in Figure 5, while G2 is not an urban cluster as its population is only 3 050 inhabitants.

Figure 6: Schematic overview identifying urban centres and urban clusters
Source: Eurostat, JRC and European Commission, Directorate-General Regional and Urban Policy and Directorate-General Agriculture and Regional Development

Step 3: identifying rural grid cells

Rural grid cells are those cells that are not identified as urban centres or as urban clusters. The majority of rural grid cells have a population density that is less than 300 inhabitants per km², although this is not necessarily the case. Some rural grid cells may have a higher number of inhabitants if they do not form part of a cluster that meets the criteria for an urban centre or an urban cluster.

Figure 7: Identifying rural grid cells

In Figure 7, cells A3, B4 and F1 each meet the population criterion for an urban centre (at least 1 500 inhabitants per km²), while cells B3, C2 and E1 each meet the population criterion for an urban cluster (at least 300 inhabitants per km²). Each group of contiguous grid cells (groups G1 and G2 in the right-hand side of Figure 7) may be analysed in relation to their total number of inhabitants and those groups of contiguous cells with 5 000 inhabitants or more are selected.

Figure 8: Identifying rural grid cells

In Figure 8, neither group G1 with a total population of 3 900 inhabitants, nor group G2 with a total population of 2 650 inhabitants reaches the population threshold for an urban cluster. As such, each cell in these two groups is classified as a rural grid cell, as shown on the right-hand side of Figure 8.

Note also, as mentioned above, that it is possible for grid cells with a population density of less than 300 inhabitants per km² to be classified as part of an urban centre, due to gap-filling.

Links to other spatial concepts/typologies

Cluster types are used as a basis for the following local territorial typologies:

Commuting flows may then be used to identify:

Cluster types are used as a basis for the following regional territorial typologies:

Functional urban areas may then be used as a basis for the following regional territorial typology:

Results

Map 1 provides an overview of the final classification of cluster types for a 1 km² population grid (as established in 2011). It shows that the largest concentrations of urban centres are located in western Germany, the Benelux countries and the United Kingdom.

The results in Map 1 may be compared with those for Map 12 (in the introductory chapter) which shows the population density of individual 1 km² grid cells. While aggregating information for cluster types (as done for Map 1) allows some of the noise to be removed from the map, thereby highlighting more clearly the main urban centres in the EU, it is also apparent that a considerable amount of information is lost (when compared with that shown in Map 0.12). For example, Map 0.12 shows the clear distinction that may be made contrasting the high number of uninhabited grid cells in Spain with a relatively large number of inhabited grid cells in France. By contrast, rural grid cells dominate the vast majority of both of these territories in Map 1.

Map 1: Cluster types based on 1 km² grid cells
Source: Eurostat, JRC and European Commission, Directorate-General Regional and Urban Policy and Directorate-General Agriculture and Regional Development
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