next
previous
items

Indicator Assessment

Landscape fragmentation pressure and trends in Europe

Indicator Assessment
Prod-ID: IND-450-en
  Also known as: LSI 004 , CSI 054
Created 29 Aug 2019 Published 13 Dec 2019 Last modified 13 Dec 2019
25 min read

In 2015, on average, there were around 1.5 fragmented landscape elements per km2 in the European Union [1], a 3.7 % increase compared with 2009.

Approximately 1.13 million km2, around 28 % of the area of the EU [1], was strongly fragmented in 2015, a 0.7 % increase compared with 2009.

There was less of an increase in fragmented landscape elements and in the area of strongly fragmented landscape between 2012 and 2015 than between 2009 and 2012 (1.4 and 0.18 percentage points, respectively).

Arable lands and permanent croplands (around 42.6 %) and pastures and farmland mosaics (around 40.2 %) were most affected by strong fragmentation pressure in 2015 in the EU. Between 2009 and 2015, however, the largest increase in the area of strongly fragmented landscape was in grasslands/pastures and in farmland mosaics.  

Luxembourg (91 %), Belgium (83 %) and Malta (70 %) had the largest proportions of strongly fragmented landscape in 2015 (as a proportion of their country area). The Baltic countries and Finland and Sweden were on average the least fragmented countries in the EU.

Between 2009 and 2015, the area of strongly fragmented landscape increased most in Croatia, as well as in Greece, Hungary and Poland.


[1] Romania is excluded because of the poor coverage of fragmentation geometry data in 2009.

 

Landscape fragmentation status and trends, 2009-2015: overview

Effective mesh density
Area of strongly fragmented landscape
Strongly fragmented landscape
Relative change in nr. of meshes
Change in strongly fragmented area (km²)
Change in strongly fragmented area (%)
Table

This indicator measures fragmentation as the density of continuous, i.e. unfragmented, semi-natural landscape elements (i.e. meshes). This is calculated by dividing the number of meshes with a unit area, e.g. 1 or 1 000 km2. If the landscape is not fragmented, i.e. it consists of a completely continuous landscape, the mesh density is 1. If the number of natural and semi-natural landscape elements in a unit area increases, the landscape becomes more fragmented and the mesh density increases.

Cities and towns are the most fragmented areas in the European landscape, as the contiguity of natural and semi-natural areas is most disrupted here because of settlements and road networks. Analysing fragmentation status and the increase in landscape areas that are fragmented to the highest level would not provide any added value in the understanding of fragmentation in Europe. It is in other areas, with lower population densities and hence more undisturbed landscape areas, that land functions such as habitat provision for biodiversity will suffer most from increasing fragmentation. Therefore, in this assessment urban centres with a population of over 50 000 and towns with a dense or semi-dense urban cluster were excluded from the analysis.

In 27 of the 28 EU Member States (EU-28) [1] in 2009, the area-weighted average mesh density was 1.43 meshes/km2. The density of meshes, and hence the fragmentation of the (less urbanised) landscape, had increased to, on average, 1.46 meshes/km2 by 2012 and 1.48 meshes/km2 by 2015. Hence, there were almost two fragmented habitats per km2 in the EU in 2015. Although these statistics show that the fragmentation of the landscape increased during the 3-year period 2009-2012, the increase slowed down after 2012, by 1.4 percentage points (from a fragmentation increase of 2.7 % during 2009-2012 to an increase of 1.3 % during 2012-2015). In total, the increase in fragmented landscape elements amounted to 3.7 % during 2009-2015. In all observation years, the fragmentation of the EEA-39 region [2] was less than that of the EU-28 region, with 1.35 meshes/km2 in 2009 and 1.39 meshes/km2 in 2015.

Approximately 1.12 million km2 of the EU was strongly fragmented in 2009, that is, an area of approximately 1.12 million km2 was affected by fragmentation with a high or very high impact (> 50 meshes/1 000 km2). This amounted to around 27.6 % of the EU-28 territory. By 2012, an additional area of around 5.6 thousand km2 was turned into strongly fragmented landscape. Between 2012 and 2015, fragmentation increased to a lesser extent, with approximately 2 000 km2 becoming strongly or very strongly fragmented during this period. With that, by 2015, around 27.8 % of the landscape in the EU was strongly or very strongly fragmented. In the 6-year period 2009-2015, a total of 7 649 km2 of the EU territory became strongly or very strongly fragmented, amounting to a 0.68 % increase in the area of strongly fragmented landscape.


[1] Romania is excluded because of the poor coverage of fragmentation geometry data in 2009.


[2] Excluding Albania, Bosnia and Herzegovina, Cyprus, Iceland, Kosovo under UN Security Council Resolution 1244/99, North Macedonia, Romania, Serbia and Turkey because of the poor coverage of fragmentation geometry data in 2009.

 

Landscape fragmentation status and trends, 2009-2015: affected lands

Number of fragmented landscape elements
Strongly fragmented landscape
Relative change in number of meshes
Change in strongly fragmented area
Table

In all observation years, on average, pastures and mosaic farmlands were most fragmented in the EU-28 [1] (calculated as the area-weighted average mesh density). Their fragmentation increased from 0.678 meshes/km2 in 2009 to 0.701 meshes/km2 in 2015. Arable lands and permanent crops had the second highest fragmentation on average, reaching 0.5 meshes/km2 by 2015. With regard to the strongest fragmentation pressure, however, arable lands and permanent crops were most affected in all years; around 42 % of their area was affected by strong urban and road infrastructure expansion, whereas very strong fragmentation affected only around 40 % of pastures and mosaic farmlands.

On average, forests were the least fragmented land cover type in the EU (approximately 0.100 meshes/km2) but strong fragmentation covered almost 16 % of forest areas, the third highest after agricultural land and pastures/mosaic farmlands. In contrast, although wetlands were the third most fragmented land cover type on average (0.320 meshes/km2), in all years, only around 3 % of their area was affected by strong fragmentation pressure. Natural grasslands, heathlands and sclerophyllous vegetation had low levels of fragmentation on average (approximately 0.100 meshes/km2) and only around 6 % of their area was affected by very strong fragmentation.

Whereas fragmentation increased for all land cover types, this increase was slower during 2012-2015 than during 2009-2012. For arable lands and permanent crops, the fragmentation increased (increase in the number of meshes/km2) on average by 4.4 % during 2009-2012 but only by 1.3 % during 2012-2015. Comparable drops in the rates of the fragmentation increase were seen for natural grasslands, heathlands and sclerophyllous vegetation (from 3.9 % to 1.7 %), for pastures and mosaic farmlands (from 3.8 % to 1 %), and for forests and transitional woodlands (from 3.7 % to 1.2 %). The fragmentation increase slowed down the most for arable lands and permanent crops, by 3.03 percentage points. The increase slowed down by 2.85 percentage points for pastures and mosaic farmlands and by 2.5 percentage points for forest and transitional woodlands.

The strongest increase in the area of most fragmented landscape was seen in natural grasslands, heathlands and sclerophyllous vegetation, which increased by 3.1 % during 2009-2012 and 1.2 % during 2012-2015. The area under strong fragmentation pressure was very small here in 2009, hence the relatively high increase. During 2012-2015, the increase was 1.7 percentage points less than during 2009-2012 and hence the general trend of slowing down was also observable in these areas. Nevertheless, grasslands are hotspots for biodiversity and have a strong carbon-sink potential; therefore, policy measures should concentrate on preserving the integrity of these areas. The most fragmented areas of arable lands and permanent crops increased the least (only 0.3 % during 2009-2015) because fragmentation was already high for these land cover types in all observation years. Wetlands were the only land cover class for which the area under strong fragmentation pressure decreased during 2009-2012 (by 1.2 %). There was a 1.5 % increase in the strongly fragmented wetland area during 2012-2015, however; therefore, during the entire observation period, the increase was 0.3 %.

 

[1] Romania is excluded because of the poor coverage of fragmentation geometry data in 2009.

Landscape fragmentation status and trends, 2009-2015: country comparison

Average number of meshes per km2
Data sources:
Area of strongly fragmented landscape (in % of country area)
Data sources:
Fragmentation change (in % of 2009 seff value)
Data sources:
Change of strongly fragmented landscape area (in % of 2009)
Data sources:
Table
Data sources:

In all observation years, Malta, Belgium, Luxembourg and the Netherlands had the most fragmented landscapes (calculated as the area-weighted average mesh density). In Malta, there were around 8.3 fragmented landscape patches per km2, the highest among all the countries. In Belgium, Luxembourg and the Netherlands, there were around 5 landscape elements per km2, on average. Locally, areas with more than 50 landscape elements per 1 000 km2 are considered very strongly fragmented (based on a statistical distribution; see methodology section). Even though Luxembourg was not, on average, the most fragmented country in the EU-28, it had the largest proportion of strongly fragmented landscape, with approximately 91 % of the country's area being strongly fragmented. In Belgium, as much as 83 % of the country's area was strongly fragmented in all 3 years (2009, 2012 and 2015). In Malta, despite having the highest average fragmentation level in the EU, the strongly fragmented landscape covered less, only approximately 70 %, of the country's area. In absolute terms, France and Germany had the largest areas of strongly fragmented landscape, with 323 000 km2 and 226 000 km2 being strongly fragmented, respectively. In terms of absolute values, Luxembourg and Malta had the smallest areas of strongly fragmented landscape, even though these areas covered a large proportion of the territory of these small countries.

The Baltic countries (Estonia, Latvia and Lithuania) and Finland and Sweden were on average the least fragmented countries in the EU, in all observation years. In all these Nordic and north-eastern countries, the effective mesh density was less than 0.5 meshes per km2, or 1 mesh per every 0.5 km2. This means that on average the non-fragmented landscape elements in these countries were at least 0.5 km2 in size. In these countries, the proportions of strongly fragmented landscape were also very small, at around or less than 10 % of each country's area.   

Although Poland was on the lower end in terms of average landscape fragmentation, as well as in terms of the largest area of strongly fragmented landscape, it showed the highest increase in average landscape fragmentation during 2009-2015. Altogether, landscape fragmentation increased by 11 % here, almost 7 % during 2009-2012 and approximately 4 % during 2012-2015. Other eastern European countries such as Croatia, Hungary and Slovakia also showed strong increases in country-average fragmentation values. These countries however had lower landscape fragmentation levels in 2009 than the European average and, as Fig. 4 (average number of meshes and area of strongly fragmented landscape) shows, even with the relatively strong increase in landscape fragmentation in these countries, fragmentation was still below the European average in 2015. Although Malta was one of the most fragmented countries, the increase in fragmentation in Malta was the lowest in the EU during 2009-2015.

Considering only the area of strongly fragmented landscape during the period 2009-2012, Croatia increased the area of very strongly fragmented landscape the most. The area of very strongly fragmented landscape increased by almost 70 %, from 11.9 % to 20.1 % of the country's area and from 6 627 km2 to 11 192 km2 in absolute terms. In Greece, Hungary and Portugal, the areas of strongly fragmented landscape also increased more than in other countries, especially during 2009-2012. This amounted to an 8 % increase in the size of the strongly fragmented area in Hungary and an approximately 5 % increase in Greece and Portugal (compared with 2009 values).

Supporting information

Indicator definition

This indicator measures landscape fragmentation due to transport infrastructure and sealed areas. Unlike the previous indicator on fragmentation status, this updated version uses the TeleAtlas® Multinet data set to ensure the statistical comparability of the time series. While the Open Street Map data set is a valuable source of the street network available for the general public, there are still inconsistencies in this data set for some regions of Europe, which render it secondary to the TeleAtlas data set.

As in the previous version, this indicator is based on the effective mesh size method (Jaeger, 2000). For some species, the effective mesh size (meff) can be interpreted as the area that is accessible when beginning to move from a randomly chosen point inside a landscape without encountering anthropogenic barriers such as transport routes or built-up areas. However, it should be stressed that for many species that can fly, or are effective dispersers in others ways, man-made structures may not act as barriers. The combination of all barriers in a landscape is referred to as the fragmentation geometry (FG) hereafter.

The meff value expresses the probability that any two points chosen randomly in an area are connected. Hence, meff is a measure of landscape connectivity, i.e. the degree to which movements between different parts of the landscape are possible. The larger the meff, the more connected the landscape. The indicator addresses the structural connectivity of the landscape and does not tackle functional, species-specific connectivity.

The effective mesh density (seff) is a measure of landscape fragmentation, i.e. the degree to which movement between different parts of the landscape is interrupted by fragmentation geometry. It gives the effective number of meshes (or landscape patches) per 1 000 km2, in other words the density of the meshes. The seff value is 1 000 km2/meff, hence the number of meshes per 1 000 km2. The more barriers fragmenting the landscape, the higher the effective mesh density.

The values of meff and seff are reported within the cells of a 1 km2 regular grid.

The value of meff is area-proportionally additive, hence it characterises the fragmentation of any region considered, independently of its size, and thus can be calculated for a combination of two or more regions. It has several advantages over other metrics:

  • It addresses the entire landscape matrix instead of addressing individual patches.
  • It is independent of the size of the reporting unit and its values can be compared among reporting units of differing sizes.
  • It is suitable for comparing the fragmentation of regions with differing total areas and with differing proportions occupied by housing, industry and transportation structures.
  • Its reliability has been confirmed on the basis of suitability criteria through a systematic comparison with other quantitative measures. The suitability of other metrics is limited, as they only partially meet the following criteria:
    • intuitive interpretation;
    • mathematical simplicity;
    • modest data requirements;
    • low sensitivity to small patches;
    • detection of structural differences;
    • mathematical homogeneity (i.e. intensive or extensive).

Units

Values of meff are positive real numbers, where 0 stands for grid cells completely covered by urban areas and infrastructure (i.e. the landscape is covered by impermeable surfaces). The lower threshold for meff is 0.000001 km2 (= 1 m2), and smaller values are rounded to this value. The highest possible value of meff is limited by the area of the landscape patches as well as by the area of the fragmentation geometry affecting the landscape patches. A landscape patch is defined as a continuous area with the barriers of the fragmentation geometry as boundaries. Hence, the largest meff value will be assigned to the largest continuous landscape patch with the smallest area taken up by the fragmentation geometry (see illustration in "Methodology for indicator calculation" section).

The seff values are positive real numbers. If meff = 0.000001 km2, then seff = 1 000 000 000 meshes per 1 000 km2. For grid cells completely covered by built-up areas and infrastructure (i.e. where meff = 0 km2), the seff value is set to -2, i.e. -2 represents positive infinity.

For convenience and practical considerations, meff values of < 0.01 km2 (= 10 000 m2) are rounded to 0, as these values are too small to be measurable without noise on a European scale. As a consequence, the largest reported seff value is 100 000 (= 1 000 km2/0.01 km2) meshes per 1 000 km2.

This indicator presents seff, rather than meff, values because these are more intuitive to understand as indications of fragmentation. For the assessment, seff values were grouped into five fragmentation classes (very low, low, medium, high and very high) by performing the following steps:

(1)                selecting 95 % of the seff value range (ignoring the upper and lower 5th percentiles);

(2)                running geometric interval classification;

(3)                rounding threshold values for straightforward comparisons and change detection.

The thresholds for the fragmentation classes are outlined below.

seff values  (number of meshes per  1 000 km2)

Fragmentation class

0-1.5

Very low

1.5-10

Low

10-50

Medium

50-250

High

> 250 seffs

Very high


 

Policy context and targets

Context description

Priority objective 1, paragraph 23, of the Seventh Environment Action Programme (7th EAP) explicitly lists fragmentation as one of the key elements necessary to protect, conserve and enhance the Union’s natural capital: 'The degradation, fragmentation and unsustainable use of land in the Union is jeopardising the provision of several key ecosystem services, threatening biodiversity and increasing Europe’s vulnerability to climate change and natural disasters. It is also exacerbating soil degradation and desertification.'

Furthermore, priority objective 7 ('To improve environmental integration and policy coherence'), paragraph 87, offers ample space for fragmentation to play a role in the more effective integration of environmental and climate-related considerations into other policies: 'Incorporation of the green infrastructure can also help to overcome the fragmentation of habitats, preserve and restore ecological connectivity, enhance ecosystem resilience and thereby ensure the continued provision of ecosystem services, including carbon sequestration, and climate adaptation, while providing healthier environments and recreational spaces for people to enjoy.'

The EU 2020 biodiversity strategy, specifically target 2, indirectly addresses the fragmentation of ecosystems and habitats, as it requires that 'by 2020, ecosystems and their services are maintained and enhanced by establishing green infrastructure and restoring at least 15 % of degraded ecosystems'.

Reducing fragmentation will also contribute to achieving all other targets of the EU biodiversity strategy, such as target 1 concerning the full implementation of the Birds and the Habitats Directives. In particular, paragraph 1 of Article 3 of the Habitats Directive sets up the legal framework for the Natura 2000 network, and paragraph 3 states that 'Where they consider it necessary, Member States shall endeavour to improve the ecological coherence of Natura 2000 by maintaining, and where appropriate developing, features of the landscape which are of major importance for wild fauna and flora, as referred to in Article 10.'

In addition, Article 6.4 of the Habitats Directive stipulates that Member States are to take 'all compensatory measures necessary to ensure that the overall coherence of the Natura 2000 network is protected'. Article 10 of the Habitats Directive and Article 3 of the Birds Directive also include more general connectivity provisions that relate to land use planning and development policies. Work on the fragmentation of ecosystems and habitats will also contribute to achieving targets 3 and 4 of the EU 2020 biodiversity strategy concerning maintaining and enhancing biodiversity in the wider countryside (and the marine environment).

[1] EEA, 2014, Fragmentation: Overview of the knowledge base in the field of habitat and landscape fragmentation.

Targets

None of the existing EU policies sets quantitative targets for reducing and/or measuring the harmful impacts of the fragmentation of ecosystems. The EU 2020 biodiversity strategy, specifically target 2, directly addresses the fragmentation of ecosystems and habitats, as it requires that 'by 2020, ecosystems and their services are maintained and enhanced by establishing green infrastructure and restoring at least 15 % of degraded ecosystems'. 

Combating fragmentation will contribute to achieving all other targets of the EU biodiversity strategy as well, such as target 1 concerning the full implementation of the Birds and the Habitats Directives. In particular, paragraph 1 of Article 3 of the Habitats Directive sets up the legal framework for the Natura 2000 network, whereas paragraph 3 states that 'Where they consider it necessary, Member States shall endeavour to improve the ecological coherence of Natura 2000 by maintaining, and where appropriate developing, features of the landscape which are of major importance for wild fauna and flora, as referred to in Article 10.'

In addition, Article 6.4 stipulates that Member States are to take 'all compensatory measures necessary to ensure that the overall coherence of Natura 2000 is protected'. Article 10 of the Habitats Directive and Article 3 of the Birds Directive also include more general connectivity provisions that relate to land use planning and development policies. Work on the fragmentation of ecosystems and habitats will also contribute to achieving targets 3 and 4 of the EU 2020 biodiversity strategy concerning maintaining and enhancing biodiversity in the wider countryside and the marine environment.

Related policy documents

 

Methodology

Methodology for indicator calculation

The calculation of the effective mesh size (meff) is based on three spatial data sets: (1) the 'landscape' extent, (2) the fragmentation geometry (FG) (landscape elements representing man-made barriers) and (3) reporting units (spatial units for which meff is calculated). The following steps are followed in computing the indicator.

Step 1: landscape extent

The 'landscape' for the calculation of meff is the seamless area of Europe. The input for this step is the Copernicus high resolution layer (HRL) on imperviousness density (IMD) from 2012 [1].

Step 2: fragmentation geometry

Fragmentation geometries are man-made landscape elements, which divide the landscape into unconnected patches. Only anthropogenic elements are considered because the indicator addresses fragmentation of the landscape in urban areas and from transport infrastructure (road and rail).

Step 2.1: fragmentation geometry — built-up areas

Built-up areas are excluded during the 'landscape extent' preparation step. From this layer, a binary mask is created and pixels with IMD values of > 30 % are deleted from the data set. 

Step 2.2: fragmentation geometry — road network

The data set representing the transportation network must meet the following technical requirements:

  1. It has to be methodologically stable, so that changes in time represent real changes and not the level of data set completion.
  2. The nomenclature/classes of roads must be clearly defined, and consistent over time, to allow different levels of fragmentation detail.
  3. It must be topologically correct, i.e. it must not contain discontinuities.
  4. It must enable the differentiation of landscape elements that have a major impact on the resulting connectivity or isolation of patches, such as tunnels, overpasses, etc. (where such elements occur, landscape patches may in fact be interconnected and thus the value of fragmentation can be considerably different).
  5. It must be based on regularly updated and if possible open source data streams to ensure the sustainability of the indicator.

The TeleAtlas® Multinet data set]was used to process the road network fragmenting geometry. The following road/rail classes were included (road class numbering is based on FRC attribute values):

0 — motorway, freeway
1 — major road less important than a motorway
2 — other major road
3 — secondary road
4 — local connecting road

Railroads

The line vectors were buffered according to the road classes to create polygon objects. Buffer sizes were selected according to the road class they represent. Buffering was also applied to prevent small topological inconsistencies in the TeleAtlas data set.

Table 1: Buffers applied to the various TeleAtlas road and rail classes

TeleAtlas road class

Buffer width (in m) on either side of the roads

Motorway, freeway

15

Major road less important than a motorway

10

Other major road

7.5

Secondary road

5

Local connecting road

2.5

Railroad

2


The result of step 2 is a fragmentation geometry layer that contains landscape patches (i.e. polygons representing the remaining non-fragmented areas) and gaps (no value), in locations where fragmentation geometries were deleted from the landscape.

 

Step 3: calculation of meff

The meff values are calculated for all reporting units. The reporting units are 1 km2 grid cells corresponding to the EEA’s accounting grid. It should be noted that any regular (i.e. larger or smaller grids) or irregular (e.g. NUTS (Nomenclature of Territorial Units for Statistics) regions) reporting units can be chosen for the calculation as long as the spatial detail is satisfactory for the topic that the indicator is designed to support. To calculate meff, the cross-boundary calculation (CBC) procedure is used (Moser et al., 2007). In the CBC process, not only the area of the landscape patch that falls inside the reporting unit is an input to the computation, but the whole area of that given landscape patch is accounted for (see image below). Hence, the borders of analytical units themselves do not influence meff values (see detailed explanation in Moser et al., 2007).

Schematic illustration for calculating the value of meff

Methodology for gap filling

The Copernicus HRL is based on satellite imagery classification. As such, there are areas assigned with no IMD values because of cloud coverage (satellite data sets are sometimes not cloud free). These gaps in the data set are filled using the Corine Land Cover (CLC) data set using the corresponding build-up mask derived from CLC classes. These are:

  • 1.1. continuous urban fabric, discontinuous urban fabric;
  • 1.2. industrial and commercial units, road and rail networks and associated land, port areas and airports;
  • 1.3. mineral extraction sites, dump sites and construction sites;
  • 1.4.2. sport and leisure facilities (only included if they were completely surrounded by the previous classes);
  • 4.2.2. salines.

Methodology references

 

Uncertainties

Methodology uncertainty

The methodology is without any major uncertainty. Some critique might arise regarding the fragmentation geometries, which were included (or not included) as barriers. This is however not a methodological uncertainty of meff and seff, but is rather a matter of consciously addressing the spatial detail of the indicator.

Data sets uncertainty

Uncertainty of the Copernicus HRL IMD data set: clouds are contained in the data layer. Corresponding Copernicus CLC data are used for the map filling (see 'Methodology for gap filling' section). Because the spatial resolutions of the HRL IMD and CLC data are different, the spatial detail of the indicator may be influenced for the cloudy area. The metadata layer is part of the indicator data set indicating HRL IMD cloud areas. 

Uncertainty of the Open Street Map (OSM) data set: the maturity, completeness and classification stability of the OSM data set are critical features for monitoring indicator changes and trends. Based on the OSM stability analysis done in 2016 (see link below), these qualities have been confirmed. Nevertheless, as OSM is a collaborative project providing crowd-sourced data under the Open Database Licence, the data set will have to be carefully analysed before any subsequent indicator update.

https://forum.eionet.europa.eu/etc-urban-land-and-soil-systems/library/10.-ap-2018/1.8.1.4-re-analysis-landscape-fragmentation-time-series/osm-stability-analysis-document

Rationale uncertainty

There is no rationale uncertainty.

Data sources

Other info

DPSIR: Pressure
Typology: Descriptive indicator (Type A - What is happening to the environment and to humans?)
Indicator codes
  • LSI 004
  • CSI 054
Frequency of updates
Updates are scheduled every 3 years
EEA Contact Info info@eea.europa.eu

Permalinks

Geographic coverage

Temporal coverage

Dates

Topics

Tags

Document Actions