Copernicus Land Monitoring Service - High Resolution Layers - Imperviousness

Data
Prod-ID: DAT-14-en
Created 22 Nov 2017 Published 15 May 2018 Last modified 13 Dec 2019
3 min read
Topics: , ,
The high resolution imperviousness products capture the percentage and change of soil sealing. Built-up areas are characterized by the substitution of the original (semi-) natural land cover or water surface with an artificial, often impervious cover. These artificial surfaces are usually maintained over long periods of time. A series of high resolution imperviousness datasets (for the 2006, 2009, 2012 and 2015 reference years) with all artificially sealed areas was produced using automatic derivation based on calibrated Normalized Difference Vegetation Index (NDVI). This series of imperviousness layers constitutes the main status layers. They are per-pixel estimates of impermeable cover of soil (soil sealing) and are mapped as the degree of imperviousness (0-100%). Imperviousness change layers were produced as a difference between the reference years (2006-2009, 2009-2012, 2012-2015 and additionally 2006-2012, to fully match the CORINE Land Cover production cycle) and are presented 1) as degree of imperviousness change (-100% -- +100%), in 20m and 100m pixel size, and 2) a classified (categorical) 20m change product.

GIS data

Imperviousness status products
  • Imperviousness 2015
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  • Imperviousness 2012
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  • Imperviousness 2009
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  • Imperviousness 2006
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Imperviousness change products
  • Imperviousness degree change 2012-2015
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  • Imperviousness classified change 2012-2015
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  • Imperviousness degree change 2009-2012
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  • Imperviousness classified change 2009-2012
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  • Imperviousness degree change 2006-2009
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  • Imperviousness classified change 2006-2009
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  • Imperviousness degree change 2006-2012 (CLC Synchronous)
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  • Imperviousness classified change 2006-2012 (CLC Synchronous)
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Metadata

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Relation:
Derived data set:  Landscape fragmentation Effective Mesh Density time-series: major and medium anthropogenic fragmenting elements (FGA2-S)
Derived data set:  Ecosystem types of Europe
information.png Temporal coverage:
information.png Geographic coverage:
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information.png Geographic accuracy:
100m, 20m
information.png Tags:
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information.png Rights:
Access to data is based on a principle of full, open and free access as established by the Copernicus data and information policy Regulation (EU) No 1159/2013 of 12 July 2013. This regulation establishes registration and licensing conditions for GMES/Copernicus users. Free, full and open access to this data set is made on the conditions that:

1.When distributing or communicating Copernicus dedicated data and Copernicus service information to the public, users shall inform the public of the source of that data and information.

2.Users shall make sure not to convey the impression to the public that the user's activities are officially endorsed by the Union.

3.Where that data or information has been adapted or modified, the user shall clearly state this.

4.The data remain the sole property of the European Union. Any information and data produced in the framework of the action shall be the sole property of the European Union. Any communication and publication by the beneficiary shall acknowledge that the data were produced “with funding by the European Union”.
information.png Coordinate reference system:
EPSG:3035
information.png Data sources

Data delivered by the external service provider.

information.png Owners:
European Union
information.png Processors:
European Environment Agency (EEA)

Additional information

 

 

 

Related content

Data

Landscape fragmentation Effective Mesh Density time-series: major and medium anthropogenic fragmenting elements (FGA2-S) The datasets below correspond to a new version of the Effective Mesh Density (seff) 2016 dataset with improved input data, for the years 2009, 2012 and 2015. This time-series uses the Copernicus Imperviousness and the TomTom TeleAtlas datasets as fragmenting geometries. The Effective Mesh Density (seff) is a measure of the degree to which movement between different parts of the landscape is interrupted by a Fragmentation Geometry (FG). FGs are defined as the presence of impervious surfaces and traffic infrastructure, including medium sized roads. The more FGs fragment the landscape, the higher the effective mesh density hence the higher the fragmentation. An important consequence of landscape fragmentation is the increased isolation of ecosystem patches that breaks the structural connections and decreases resilience and ability of habitats to provide various ecosystem services. Fragmentation also influences human communities, agriculture, recreation and overall quality of life. Monitoring how fragmentation decreases landscape quality and changes the visual perception of landscapes provides information for policy measures that aim at improving ecosystem condition and restoration as well as maintaining the attractiveness of landscapes for recreational activities. The geographic coverage of the datasets is EEA39.
Ecosystem types of Europe The dataset combines the Copernicus land service portfolio and marine bathymetry and seabed information with the non-spatial EUNIS habitat classification for a better biological characterization of ecosystems across Europe. As such it represents probabilities of EUNIS habitat presence for each MAES ecosystem type.

Figures produced

Interactive charts

Interactive maps produced

Produced Indicators

Used in indicators

Landscape fragmentation pressure and trends in Europe 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 km 2 , in other words the density of the meshes. The seff value is 1 000 km 2 /meff, hence the number of meshes per 1 000 km 2 . 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 km 2 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).
Landscape fragmentation pressure from urban and transport infrastructure expansion This indicator is based on the Effective Mesh Size (Jaeger 2000) method .  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 man-made 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 called 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 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 km 2 , in other words, the density of the meshes. The seff value is calculated as 1 000 km 2 /meff, hence, the number of meshes per 1 000 km 2 . The more barriers fragmenting the landscape, the higher the effective mesh density. meff and seff are reported within the cells of a 1 km 2 regular grid. 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. The meff 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. It's reliability has been confirmed on the basis of suitability criteria through a systematic comparison with other quantitative measures. The suitability of other metrics was limited as they only partially met 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).
Imperviousness and imperviousness change The imperviousness indicator is defined as the yearly average imperviousness change between two reference years, as measured by imperviousness change products. The change is aggregated for a certain reference unit and expressed as relative to the size of that unit (as a percentage). The imperviousness change value for a 100 m raster cell is based on 100 m imperviousness change products. The default reference unit is the country, but the indicator can be aggregated based on different spatial units. For example, for a certain country, a n imperviousness indicator value of 0.2 %, means that on average, an additional 0.2 % of this country's area has been sealed annually during the period between the two reference years in question. If above a certain rate of increase (threshold values) , this value can be used as a warning sign. The aggregation of imperviousness values to reference units is performed using the LEAC CUBE method.
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