Detailed Methodology of the Revised Degree of Urbanisation Classification

DETAILED METHODOLOGY OF THE REVISED DEGREE OF URBANISATION CLASSIFICATION TABLE OF CONTENTS

TABLE OF CONTENTS...... 2

INTRODUCTION...... 3

1. CLASSIFICATION OF LOCAL ADMINISTRATIVE UNITS (LAU2S)....3 1.1. Rural vs. non-rural...... 3 1.2. Classify non-rural in intermediate and urban...... 4 2. REFINEMENT OF THE CLASSIFICATION AT LAU2 LEVEL...... 5 2.1. LAU2 without a raster equivalent...... 6 2.2. LAU2 with no population in the raster equivalent...... 6 2.3. Border effects...... 7 2.3.1. Small LAU2s classified as "Rural" but with high share of urban cluster...... 7 2.3.2. LAU2s classified as "Urban'" or "Intermediate" but with low share of urban cluster and a low total population...... 8 ANNEX 1 - LAU2S WITH NO POPULATION GRID BUT HIGH CENSUS DENSITY...... 9

2 INTRODUCTION

This section describes a methodology for classifying local administrative units (LAU2) in thinly (rural), intermediate and densely populated (urban) areas. This methodology has been developed by DG AGRI and DG REGIO

1. CLASSIFICATION OF LOCAL ADMINISTRATIVE UNITS (LAU2S)

The classification is based on a 1 km² population grid. This grid is already available for Denmark, Sweden, Finland, Austria and the Netherlands and the classification is based on the real grid in these Member States. For the remaining Member States, the classification relies on the population disaggregation grid created by the JRC (version 5) based on LAU2 population and CORINE land cover.

The 1 km² grid is likely to become the future standard and has the benefit that it can easily be reproduced in countries outside the EU. For example, this classification can also be applied to Switzerland, Norway and Croatia following the exact same approach.

Because the CORINE land cover map does not cover the four French overseas regions and Madeira and Açores in Portugal, the population disaggregation grid does not cover these regions. Therefore, the classification for these regions is done following the original degree of urbanisation methodology.

Because the CORINE land cover map does not cover the four French overseas regions and Madeira and Açores in Portugal, the population disaggregation grid does not cover these regions. Therefore, the classification for these regions will be discussed separately.

In a first step, we divide LAU2s in rural and non-rural. Non-rural LAU2s are then furthermore divided in intermediate and urban LAU2s.

1.1. Rural vs. non-rural

We define a LAU2 as a rural LAU2 if less the 50% of the population is living in an urban cluster.

An urban cluster is defined as an area that has

 A population at least 300 habitants in all its cells, thus a population density of at least 300/km² in all the area.  At least 5000 people in the area.

The calculation thus goes in two steps:

First, we select all cells that have a population of more then 300. These cells will be combined in contiguous groups, that is to say for each cell with over 300 inhabitants, we will check if one of the cells it is touching also has over 300 inhabitants (including diagonal touching). If so, that cell is added to the same group (see figure below).

Within the groups, we can now count the total population and select those groups that have more then 5000 people. These are urban clusters.

We can now overlay the LAU2 units with this urban cluster. This allows us to calculate the population of each LAU2 that lives in an urban cluster. We compare this to the total population of the LAU2. If less then 50% is living in an urban cluster, the LAU2 is classified as rural.

1.2. Classify non-rural in intermediate and urban

The proposed methodology intends to provide an alternative to the existing typology of "degree of urbanisation", as defined in the EU Labour Force Survey. The "degree of urbanisation" typology distinguishes three categories of local units. Hence, the new methodology also proposes three categories of LAU2 units, by further classifying non- rural LAU2 units in "intermediate" and "urban" LAU2s.

To make distinction between urban and intermediate we classify as urban those LAU2s where 50% or more of the population lives in a high-density cluster.

We define a high-density cluster as a non-diagonal contiguous cluster of having more then 50000 people and a population density of 1500hab/km2 or more.

Additionally, we ensure that all high-density clusters have at least 75% of their population in urban LAU2s by adding 25 LAU2s to the urban category.

The calculation of the high-density cluster is similar to the urban cluster calculation. First, we select all cells that have a population of more then 1500. These cells will be combined in contiguous groups, that is to say for each cell with over 1500 inhabitants, we will check if one of the cells it is touching also has over 1500 inhabitants (not including diagonal touching). If so, that cell is added to the same group. We then apply a gap- filling algorithm that fills up gaps within the cluster and smoothens sharp borders (see figure below).

4 Clusters before filling Clusters after filling.

Cluster with less then 50 000 people were removed, giving the final high-density clusters.

We can now overlay the non rural LAU2 units with these high-density clusters. This allows us to calculate the population of each LAU2 that lives in a high-density cluster. We compare this to the total population of the non rural LAU2. If more than 50% is living in a high-density cluster, the LAU2 is classified as urban.

2. REFINEMENT OF THE CLASSIFICATION AT LAU2 LEVEL

The methodology presents some problem and exceptions due to the spatial resolution and in some cases the quality of the data used for the classification.

Generally the solution proposed is based on the share of urban cluster to identify the exceptions and to re-classify possible misclassifications.

2.1. LAU2 without a raster equivalent

By creating the LAU2s grid, 830 LAU2s (EU-27 plus Switzerland, Norway, Croatia, Monaco, Vatican and San Marino) have no raster equivalent due to their small size (i.e. no cells were attributed to these LAU2s).

5 These LAU2s have been classified taking in account the share of urban cluster within the LAU2s by intersecting the LAU2s with the area of the urban clusters.

For this purpose, the two types of clusters, high-density clusters (density>1.500 inh/km² total population >50000) and urban clusters (density > 300 inh/km² and total population > 5000), are taken in account.

The rules for the classification are:

"Rural" if the urban cluster does not cover the LAU2 (163 LAU2s)

"Urban" if the area share of the LAU2 is more than 50% inside high-density cluster(s) (384 LAU2s).

"Intermediate" if the area share of the LAU2 is more than 50% inside urban cluster(s) (283 LAU2s).

Here are some examples of non rasterized LAU2s:

2.2. LAU2 with no population in the raster equivalent

There are LAU2s with zero population according to the population grid but with a high population density according the CENSUS 2001 data. It concerns 12 LAU2s where the population grid does not reflect the correct population. Five of these were classified as rural and seven as intermediate. These cases are shown in the "Annex 1 - LAU2s with no population grid but high Census density", while below is the case of Dundalk with no population according to the grid but obviously urbanised.

6 2.3. Border effects

Due to the coarse spatial resolution (1km), compared to the relatively small size of the LAU2s, mismatching of the grid population to the right LAU2 may happen.

We resolve two kinds of misclassification: i) LAU2s classified as "Rural", but with a relatively high share of "urban'" area and ii) LAU2s classified as "Urban" or "Intermediate", with a low total grid population and a low share of "urban" area.

2.3.1. Small LAU2s classified as "Rural" but with high share of urban cluster

Analysing the share of urban cluster within the LAU2s by intersecting the LAU2s with the area of the urban clusters is possible to spot the LAU2s that are probably misclassified as Rural.

Part of urban cluster (%) Occurrence with area less than 5km² Occurrence with more than 5 km² > 50 16 1 > 40 29 1 > 30 63 8 > 20 126 74 > 10 265 549

After the evaluation of the different threshold we conclude that the Rural LAU2s with less than 5 km² area and a share of Urban cluster higher than 30 % should be reclassified (63 LAU2s).

The reclassification in Urban or Intermediate should follow the same method used for the un-rasterized LAU2s. These results in 54 LAU2s reclassified as Intermediate and 9 as Urban.

Here are some examples:

7 2.3.2. LAU2s classified as "Urban'" or "Intermediate" but with low share of urban cluster and a low total population

In LAU2s with a low total population the presence of even a single cell of urban cluster can lead to a "Urban" or "Intermediate" classification.

In the following table are shown the results using different thresholds for the total population and the share of urban cluster.

Area of urban total Occurrences census density <= 150 clusters population < 5 K 3 3 1% 5-10 K 3 3 10-15 K 11 11 < 5 K 169 163 5% 5-10 K 93 90 10-15 K 100 94 < 5 K 703 616 10% 5-10 K 406 284 10-15 K 330 233 < 5 K 1434 1112 15% 5-10 K 874 463 10-15 K 571 263

After the evaluation of the different threshold we conclude that 703 "Urban" or "Intermediate" LAU2s with less than 10 % of urban cluster area and less than 5 000 inhabitants should be reclassified as Rural. (some examples in the pictures below)

8 ANNEX 1 - LAU2S WITH NO POPULATION GRID BUT HIGH CENSUS DENSITY

For some LAU2s, there is population living on it according to the census data but not according to the population grid.

To spot these cases the following query was made:

Population (on the grid) = 0 & Census density > 0 & No intersection with urban cluster

Out of these 50 cases, 12 have a density higher than 150hab/km²:

COMM ID Name Population Density Type

CH1005002271 Meyriez 547 210 Rural

CH2208005609 Rivaz 317 228 Rural

CH2209005644 Reverolle 323 297 Rural

DE01005600025 Helgoland 1549 299 Rural

DK4011 Christiansø 102 362 Rural

IE1104147020 Dundalk No. 3 Urban 1407 559 Intermediate

IT103013040 Campione d'Italia 2267 1567 Intermediate

IT107010044 Portofino 529 2592 Intermediate

IT519084020 Lampedusa e Linosa 5725 2883 Intermediate

9 Here are some screenshots: (screenshot for each 12 cases)