Lead Image
No image
Lead Image Caption
Metadata
DPSIR
Pressure
Typology
Descriptive indicator (Type A - What is happening to the environment and to humans?)
UN SDGs
SDG15: Life on land
Topics
Land use , Soil , Biodiversity , Transport and mobility
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"text": "Land take, urban sprawl and economic activities lead to habitat fragmentation, decreasing the resilience of ecosystems. Monitoring fragmentation supports policy actions that aim to ensure remaining habitats can support biodiversity. Fragmentation affects all areas of Europe, even very sparsely populated ones. Moreover, in the EU plus the United Kingdom, 27% of land is considered highly fragmented where habitats are less than 0.02km 2 on average. However, policy measures to protect certain areas seem to be effective in preventing fragmentation, particularly in protected areas."
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"plaintext": "The extent of landscape fragmentation varies considerably by country in the EU-27+UK region, being highest in Malta, followed by the Netherlands, Belgium, Germany and Luxembourg. Malta has the most fragmented landscape by far, with 15 landscape objects per km 2 on average, which is around double the extent of landscape fragmentation in the Netherlands and Belgium, four times that of Germany and greatly above the EU-27+UK average of 1-3.5 landscape objects/km\u00b2 (95% confidence interval). Moreover, the average landscape object size in Malta is around 0.06km 2 , considerably below the EU-27+UK average of around 0.68km 2 .",
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Supporting information
Methodology
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"text": "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)."
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"text": "The TeleAtlas\u00ae Multinet data set"
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"text": "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):"
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"text": "0 \u2014 motorway, freeway\n\n1 \u2014 major road less important than a motorway\n\n2 \u2014 other major road\n\n3 \u2014 secondary road\n\n4 \u2014 local connecting road"
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"text": " grid cells corresponding to the EEA\u2019s 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 "
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{
"children": [
{
"text": "See a schematic illustration for calculating the value of "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": " "
}
],
"type": "link",
"data": {
"url": "https://www.eea.europa.eu/media/infographics/landscape-fragmentation/view"
}
},
{
"text": "."
}
],
"type": "p"
},
{
"children": [
{
"text": ""
}
],
"type": "p"
},
{
"children": [
{
"text": "Measurement unit"
}
],
"type": "h4"
},
{
"children": [
{
"text": "Values of "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": " 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 "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": " is 0.000001km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": " (= 1m"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": "), and smaller values are rounded to this value. The highest possible value of "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": " 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 "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": " 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)."
}
],
"type": "p"
},
{
"children": [
{
"text": "The "
},
{
"children": [
{
"text": "seff"
}
],
"type": "i"
},
{
"text": " values are positive real numbers. If "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": " = 0.000001km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": ", then "
},
{
"children": [
{
"text": "seff"
}
],
"type": "i"
},
{
"text": " = 1,000,000,000 meshes per 1 000km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": ". For grid cells completely covered by built-up areas and infrastructure (i.e. where "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": " = 0km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": "), the "
},
{
"children": [
{
"text": "seff"
}
],
"type": "i"
},
{
"text": " value is set to -2, i.e. -2 represents positive infinity."
}
],
"type": "p"
},
{
"children": [
{
"text": "For convenience and practical considerations, "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": " values of < 0.01km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": " (= 10 000m"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": ") 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 "
},
{
"children": [
{
"text": "seff"
}
],
"type": "i"
},
{
"text": " value is 100,000 (= 1,000km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": "/0.01km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": ") meshes per 1,000km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": "."
}
],
"type": "p"
},
{
"children": [
{
"text": "This indicator presents "
},
{
"children": [
{
"text": "seff"
}
],
"type": "i"
},
{
"text": ", rather than "
},
{
"children": [
{
"text": "meff"
}
],
"type": "i"
},
{
"text": ", values because these are more intuitive to understand as indications of fragmentation. For the assessment, "
},
{
"children": [
{
"text": "seff"
}
],
"type": "i"
},
{
"text": " values were grouped into five fragmentation classes (very low, low, medium, high and very high) by performing the following steps:"
}
],
"type": "p"
},
{
"children": [
{
"text": "(1) selecting 95% of the "
},
{
"children": [
{
"text": "seff"
}
],
"type": "i"
},
{
"text": " value range (ignoring the upper and lower 5th percentiles);"
}
],
"type": "p"
},
{
"children": [
{
"text": "(2) running geometric interval classification;"
}
],
"type": "p"
},
{
"children": [
{
"text": "(3) rounding threshold values for straightforward comparisons and change detection."
}
],
"type": "p"
},
{
"children": [
{
"text": "The thresholds for the fragmentation classes are outlined below."
}
],
"type": "p"
},
{
"children": [
{
"text": " "
}
],
"type": "p"
},
{
"children": [
{
"children": [
{
"children": [
{
"children": [
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": "seff"
}
],
"type": "i"
},
{
"text": ""
}
],
"type": "b"
},
{
"text": ""
},
{
"children": [
{
"text": " values "
}
],
"type": "b"
},
{
"text": ""
}
],
"type": "p"
},
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": "(number of meshes per 1,000km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": ")"
}
],
"type": "b"
},
{
"text": ""
}
],
"type": "p"
}
],
"type": "td"
},
{
"children": [
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": "Fragmentation class"
}
],
"type": "b"
},
{
"text": ""
}
],
"type": "p"
}
],
"type": "td"
}
],
"type": "tr"
},
{
"children": [
{
"children": [
{
"children": [
{
"text": "0-1.5"
}
],
"type": "p"
}
],
"type": "td"
},
{
"children": [
{
"children": [
{
"text": "Very low"
}
],
"type": "p"
}
],
"type": "td"
}
],
"type": "tr"
},
{
"children": [
{
"children": [
{
"children": [
{
"text": "1.5-10"
}
],
"type": "p"
}
],
"type": "td"
},
{
"children": [
{
"children": [
{
"text": "Low"
}
],
"type": "p"
}
],
"type": "td"
}
],
"type": "tr"
},
{
"children": [
{
"children": [
{
"children": [
{
"text": "10-50"
}
],
"type": "p"
}
],
"type": "td"
},
{
"children": [
{
"children": [
{
"text": "Medium"
}
],
"type": "p"
}
],
"type": "td"
}
],
"type": "tr"
},
{
"children": [
{
"children": [
{
"children": [
{
"text": "50-250"
}
],
"type": "p"
}
],
"type": "td"
},
{
"children": [
{
"children": [
{
"text": "High"
}
],
"type": "p"
},
{
"children": [
{
"text": "Very high"
}
],
"type": "p"
}
],
"type": "td"
}
],
"type": "tr"
},
{
"children": [
{
"children": [
{
"text": "> 250 "
},
{
"children": [
{
"text": "seffs"
}
],
"type": "i"
},
{
"text": ""
},
{
"children": [
{
"text": ""
}
],
"type": "i"
},
{
"text": ""
},
{
"children": [
{
"text": ""
}
],
"type": "strong"
},
{
"text": ""
}
],
"type": "p"
}
],
"type": "td"
}
],
"type": "td"
}
],
"type": "tr"
}
]
Data sources and providers
{
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"link": "https://www.eea.europa.eu/data-and-maps/data/landscape-fragmentation-indicator-effective-mesh/landscape-fragmentation-effective-mesh-density/landscape-fragmentation-effective-mesh-density-1",
"organisation": "European Environment Agency (EEA)",
"title": "Landscape fragmentation Effective Mesh Density: major and medium anthropogenic fragmenting elements (FGA2-S) - version 2.0, Nov. 2016 - INSPIRE METADATA"
}
]
}
Definition
[
{
"children": [
{
"text": "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\u00ae 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."
}
],
"type": "p"
},
{
"children": [
{
"text": " "
}
],
"type": "p"
},
{
"children": [
{
"text": "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. The combination of all barriers in a landscape is referred to as the fragmentation geometry (FG) hereafter. However, it should be stressed that for many species that can fly, or are effective dispersers in other ways, man-made structures may not act as barriers. "
}
],
"type": "p"
},
{
"children": [
{
"text": " "
}
],
"type": "p"
},
{
"children": [
{
"text": "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."
}
],
"type": "p"
},
{
"children": [
{
"text": "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 km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": ", in other words the density of the meshes. The seff value is 1,000 km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": "/meff, hence the number of meshes per 1,000 km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": ". The more barriers fragmenting the landscape, the higher the effective mesh density."
}
],
"type": "p"
},
{
"children": [
{
"text": " "
}
],
"type": "p"
},
{
"children": [
{
"text": "The values of meff and seff are reported within the cells of a 1 km"
},
{
"children": [
{
"text": "2"
}
],
"type": "sup"
},
{
"text": " regular grid."
}
],
"type": "p"
},
{
"children": [
{
"text": " "
}
],
"type": "p"
},
{
"children": [
{
"text": "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:"
}
],
"type": "p"
},
{
"children": [
{
"text": "\u00b7 It addresses the entire landscape matrix instead of addressing individual patches."
}
],
"type": "p"
},
{
"children": [
{
"text": "\u00b7 It is independent of the size of the reporting unit and its values can be compared among reporting units of differing sizes."
}
],
"type": "p"
},
{
"children": [
{
"text": "\u00b7 It is suitable for comparing the fragmentation of regions with differing total areas and with differing proportions occupied by housing, industry and transportation structures."
}
],
"type": "p"
},
{
"children": [
{
"text": "\u00b7 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:"
}
],
"type": "p"
},
{
"children": [
{
"text": "o intuitive interpretation;"
}
],
"type": "p"
},
{
"children": [
{
"text": "o mathematical simplicity;"
}
],
"type": "p"
},
{
"children": [
{
"text": "o modest data requirements;"
}
],
"type": "p"
},
{
"children": [
{
"text": "o low sensitivity to small patches;"
}
],
"type": "p"
},
{
"children": [
{
"text": "o detection of structural differences;"
}
],
"type": "p"
},
{
"children": [
{
"text": "o mathematical homogeneity (i.e. intensive or extensive)."
}
],
"type": "p"
}
]
Unit of measure
[
{
"children": [
{
"text": "See methodology for definition of "
},
{
"children": [
{
"text": "meff."
}
],
"type": "i"
},
{
"text": ""
}
],
"type": "p"
},
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": "Spatial units:"
}
],
"type": "b"
},
{
"text": " the proposed indicator is delivered as a raster data layer with cell size of 100m by 100m."
},
{
"children": [
{
"text": ""
}
],
"type": "i"
},
{
"text": ""
}
],
"type": "p"
}
]
Policy / environmental relevance
[
{
"children": [
{
"text": "In May 2020, the EU adopted a Biodiversity Strategy to 2030, related to protecting and restoring nature. The strategy states that \u2018The biodiversity crisis and the climate crisis are intrinsically linked. Climate change accelerates the destruction of the natural world through droughts, flooding and wildfires, while the loss and unsustainable use of nature are in turn key drivers of climate change\u2019. Droughts are negatively affecting agricultural ecosystems and food security, resilience of forest ecosystems and ability of green urban spaces to protect people against heat waves. In particular, the impacts of extended droughts on ecosystems need to be assessed because they can lead to significant loss of vegetation productivity and irreversible damage to the condition of ecosystems and can lead to land degradation. "
}
],
"type": "p"
},
{
"children": [
{
"text": "In February 2021, the European Commission presented the "
},
{
"children": [
{
"text": "EU adaptation strategy package"
}
],
"type": "link",
"data": {
"url": "http://ec.europa.eu/clima/policies/adaptation/what/documentation_en.htm"
}
},
{
"text": ". The new strategy sets out how the\u00a0European Union can adapt to the unavoidable impacts of climate change\u00a0and become\u00a0climate resilient by 2050. One of the objectives of the strategy is to ensure better-informed decision-making, which will be achieved by bridging knowledge gaps and further developing the European climate adaptation platform ("
},
{
"children": [
{
"text": "Climate-ADAPT"
}
],
"type": "link",
"data": {
"url": "http://climate-adapt.eea.europa.eu/"
}
},
{
"text": ") as the \u2018one-stop shop\u2019 for adaptation information in Europe"
},
{
"children": [
{
"text": " "
}
],
"data": {
"footnote": "<?xml version=\"1.0\"?>\n<div class=\"csl-bib-body\" style=\"line-height: 1.35; \">\n <div class=\"csl-entry\">EC and EEA, 2021, 'Climate-ADAPT', <i>European Commission and European Environment Agency</i> (http://climate-adapt.eea.europa.eu/) accessed March 6, 2021.</div>\n</div>\n",
"footnoteTitle": "EC, 2021, Climate-ADAPT",
"uid": "Bsg3h",
"zoteroId": "DRL66ZF2"
},
"type": "zotero"
},
{
"text": ". Climate-ADAPT has been developed jointly by the European Commission and the EEA to share knowledge on (1) observed and projected climate change and its impacts on environmental and social systems and on human health, (2) relevant research, (3) EU, transnational, national and sub-national adaptation strategies and plans, and (4) adaptation case studies. "
}
],
"type": "p"
}
]
Frequency of dissemination
1
Accuracy and uncertainties
[
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": "Methodology uncertainty"
}
],
"type": "b"
},
{
"text": ""
}
],
"type": "p"
},
{
"children": [
{
"text": "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 m"
},
{
"children": [
{
"text": "eff "
}
],
"type": "sub"
},
{
"text": "and s"
},
{
"children": [
{
"text": "eff"
}
],
"type": "sub"
},
{
"text": ", but is rather a matter of consciously addressing the spatial detail of the indicator."
}
],
"type": "p"
},
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": "Data set uncertainty"
}
],
"type": "b"
},
{
"text": ""
}
],
"type": "p"
},
{
"children": [
{
"text": "Clouds are contained in the Copernicus Land Monitoring Service 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."
}
],
"type": "p"
}
]
Settings
Short name
landscape-fragmentation-pressure-in-europe
Versioning enabled
yes
Contents
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