The environmental data centre for land use provides data to understand the relationship between land use and environmental impacts. Information is provided at different scales combining European coverage with global and in situ survey data. The core of data centre activities is related to dissemination of operational services in connection with key land cover/land use datasets, relevant indicators and derived products based on spatial analysis and change detection.
For the reference year 2015 , 85 861 km 2 of the total area covered by the EEA-39 countries were mapped and categorised as 'sealed surface' in the Copernicus imperviousness product. This corresponds to 1.466 % of the total EEA-39 area.
Between 2006 and 2015, soil sealing (imperviousness) in all EEA-39 countries increased by a total of 3 859 km2 , an annual average increase of 429 km 2 . During this period, the average annual increase in soil sealing relative to country area varied from 0 % to 0.088 %.
In 2015, the percentage of a countries' total area that was sealed also varied greatly, with values ranging from 16.17 % (Malta) to 0.07 % (Iceland). The highest sealing values, as a percentage of country area, occurred in small countries with high population densities, while the lowest sealing values can be found in large countries with low population densities.
The average annual increase in sealing was 460 km 2 between 2006-2009, increasing to 492 km 2 for the 2009-2012 period and slowing to 334 km 2 for the 2012-2015 period. The slow-down in the sealing increase between the two reference periods occurred in 31 out of 39 countries. The same trend is visible for sealing figures normalised by the size of the country (the % of the country newly sealed on average annually for the three periods).
The most problematic situation occurs in countries where there is already a high percentage of sealing and where the annual rate of increase relative to country area is high. Even more problematic are situations where, for 2012-2015, the rate of sealing increase is accelerating, in contrast to the general trend of a slowing rate of increase.
The map shows the percentage of the average annual change in soil sealing for each of the rectangular 10 km x 10 km grid cells, over the 2006-2015 period
The map shows the density of soil sealing in 2012, based on a 10 km2 reference grid. Green and light orange colors show areas with no or very limited sealing, while red and dark red colors show highly to fully sealed grid cells (mainly urban areas).
This is a collection of geospatial reference datasets published on the website and registered in EEA`s Spatial Data Infrastructure (SDI). The link under "GIS data" points to the SDI geospatial analytical reference catalogue.
Change of vegetation productivity during the years 2000-2016. Vegetation productivity was calculated for each 500m grid cell from a remote sensing derived vegetation index (PPI). The layer shows the changes expressed in % of 2000 calculated from the fitted line of the linear trend model.
The chart shows the vegetation productivity changes (%) over areas with land use change in the period 2000-2018. The values are broken down by major land use change drivers.
Vegetation productivity indicates the spatial distribution and change of the vegetation cover - a key characteristic of ecosystem condition.
Vegetation productivity in Europe on average has a regional pattern of increase and decline. Increase was observed most in South Eastern Europe, over croplands and wetlands in the Steppic region and grasslands and sparsely vegetated lands and in the Black Sea and Anatolian regions. Decline happened most over croplands and grasslands in the Atlantic region as well as over wetlands in the Alpine region.
Climate has important influence on vegetation productivity in Europe. Strongest is the influence of precipitation increase, especially in the South Eastern regions. Decreasing number of frost days increased productivity in the Pannonian region but decreased productivity in the Atlantic region.
Climatic variations are important drivers of vegetation productivity, but land use changes are even stronger. Productivity was most increased by agricultural land management and converting other lands to agriculture, whereas largest decrease was caused by sprawling urban areas.
The raster files are the time series of the start of the vegetation growing season (day of the year) and the derived linear trends (in day / year).
The start of the growing season time-series is based on the time series of the Plant Phenology Index (PPI) derived from the MODIS BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR). The PPI index is optimized for efficient monitoring of vegetation phenology and is derived from the source MODIS data using radiative transfer solutions applied to the reflectance in visible-red and near infrared spectral domains. The start of season indicator is based on calculating the start of the vegetation growing season from the annual PPI temporal curve using the TIMESAT software for each year between and including 2000 and 2016.
Many global policy frameworks, including the United Nations Sustainable Development Goals (SDGs),directly and indirectly address land and soil. Many of these SGDs cannot be achieved without healthysoils and a sustainable land use. Below is an overview of the SDGs with strong links to soil.
For visualisation purposes, the initial 100 m spatial resolution Corine Land Cover dataset was re-sampled to a 10 km2 grid. The observation periods can be visualised by activating the 'layers' icon and selecting the respective periods.
Soil contains significant amounts of carbon and nitrogen, which can be released into the atmosphere depending on how we use the land. Clearing or planting forests, the melting of permafrost can tilt the greenhouse gas emission balance one way or the other. Climate change can also substantially alter what farmers can produce and where.
This is a collection of geospatial reference datasets published on the website and registered in EEA`s Spatial Data Infrastructure (SDI). The link under "GIS data" points to the SDI geospatial analytical reference catalogue.
The raster files are the time series of the start of the vegetation growing season (day of the year) and the derived linear trends (in day / year).
The start of the growing season time-series is based on the time series of the Plant Phenology Index (PPI) derived from the MODIS BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR). The PPI index is optimized for efficient monitoring of vegetation phenology and is derived from the source MODIS data using radiative transfer solutions applied to the reflectance in visible-red and near infrared spectral domains. The start of season indicator is based on calculating the start of the vegetation growing season from the annual PPI temporal curve using the TIMESAT software for each year between and including 2000 and 2016.
The raster files are the annual above ground growing season length time-series and the derived linear trends for the period 2000-2016. The data set addresses trends in the season length of land surface vegetation derived from remote sensing observed time series of vegetation indices. The vegetation index used in the indicator is the Plant Phenology Index (PPI, Jin and Eklundh, 2014). PPI is based on the MODIS Nadir BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR. The product provides reflectance data for the MODIS “land” bands (1 - 7) adjusted using a bi-directional reflectance distribution function. This function models values as if they were collected from a nadir-view to remove so called cross-track illumination effects. The Plant Phenology Index (PPI) is a new vegetation index optimized for efficient monitoring of vegetation phenology. It is derived from radiative transfer solution using reflectance in visible-red (RED) and near-infrared (NIR) spectral domains. PPI is defined to have a linear relationship to the canopy green leaf area index (LAI) and its temporal pattern is strongly similar to the temporal pattern of gross primary productivity (GPP) estimated by flux towers at ground reference stations. PPI is less affected by presence of snow compared to commonly used vegetation indices such as Normalized Difference Vegetation Index (NDVI) or Enhanced Vegetation Index (EVI). The product is distributed with 500 m pixel size (MODIS Sinusoidal Grid) with 8-days compositing period.
The raster files are the above ground vegetation productivity time-series and the derived linear trend for the period 2000-2016.The data set addresses trends in land surface productivity derived from remote sensing observed time series of vegetation indices. The vegetation index used in the indicator is the Plant Phenology Index (PPI, Jin and Eklundh, 2014). PPI is based on the MODIS Nadir BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR. The product provides reflectance data for the MODIS “land” bands (1 - 7) adjusted using a bi-directional reflectance distribution function. This function models values as if they were collected from a nadir-view to remove so called cross-track illumination effects. The Plant Phenology Index (PPI) is a new vegetation index optimized for efficient monitoring of vegetation phenology. It is derived from radiative transfer solution using reflectance in visible-red (RED) and near-infrared (NIR) spectral domains. PPI is defined to have a linear relationship to the canopy green leaf area index (LAI) and its temporal pattern is strongly similar to the temporal pattern of gross primary productivity (GPP) estimated by flux towers at ground reference stations. PPI is less affected by presence of snow compared to commonly used vegetation indices such as Normalized Difference Vegetation Index (NDVI) or Enhanced Vegetation Index (EVI).The product is distributed with 500 m pixel size (MODIS Sinusoidal Grid) with 8-days compositing period.
Many global policy frameworks, including the United Nations Sustainable Development Goals (SDGs),directly and indirectly address land and soil. Many of these SGDs cannot be achieved without healthysoils and a sustainable land use. Below is an overview of the SDGs with strong links to soil.
Soil contains significant amounts of carbon and nitrogen, which can be released into the atmosphere depending on how we use the land. Clearing or planting forests, the melting of permafrost can tilt the greenhouse gas emission balance one way or the other. Climate change can also substantially alter what farmers can produce and where.
Europe's land and soil face a number of pressures, including urban expansion, contamination from
agriculture and industry, soil sealing, landscape fragmentation, low crop diversity, soil erosion and
extreme weather events linked to climate change.
Greener cities with cleaner energy and transport systems, a green infrastructure connecting green areas,
less intensive sustainable agricultural practices can help make Europe's land use more sustainable and
soils healthier.
For the reference year 2015 , 85 861 km 2 of the total area covered by the EEA-39 countries were mapped and categorised as 'sealed surface' in the Copernicus imperviousness product. This corresponds to 1.466 % of the total EEA-39 area.
Between 2006 and 2015, soil sealing (imperviousness) in all EEA-39 countries increased by a total of 3 859 km2 , an annual average increase of 429 km 2 . During this period, the average annual increase in soil sealing relative to country area varied from 0 % to 0.088 %.
In 2015, the percentage of a countries' total area that was sealed also varied greatly, with values ranging from 16.17 % (Malta) to 0.07 % (Iceland). The highest sealing values, as a percentage of country area, occurred in small countries with high population densities, while the lowest sealing values can be found in large countries with low population densities.
The average annual increase in sealing was 460 km 2 between 2006-2009, increasing to 492 km 2 for the 2009-2012 period and slowing to 334 km 2 for the 2012-2015 period. The slow-down in the sealing increase between the two reference periods occurred in 31 out of 39 countries. The same trend is visible for sealing figures normalised by the size of the country (the % of the country newly sealed on average annually for the three periods).
The most problematic situation occurs in countries where there is already a high percentage of sealing and where the annual rate of increase relative to country area is high. Even more problematic are situations where, for 2012-2015, the rate of sealing increase is accelerating, in contrast to the general trend of a slowing rate of increase.
Vegetation productivity indicates the spatial distribution and change of the vegetation cover - a key characteristic of ecosystem condition.
Vegetation productivity in Europe on average has a regional pattern of increase and decline. Increase was observed most in South Eastern Europe, over croplands and wetlands in the Steppic region and grasslands and sparsely vegetated lands and in the Black Sea and Anatolian regions. Decline happened most over croplands and grasslands in the Atlantic region as well as over wetlands in the Alpine region.
Climate has important influence on vegetation productivity in Europe. Strongest is the influence of precipitation increase, especially in the South Eastern regions. Decreasing number of frost days increased productivity in the Pannonian region but decreased productivity in the Atlantic region.
Climatic variations are important drivers of vegetation productivity, but land use changes are even stronger. Productivity was most increased by agricultural land management and converting other lands to agriculture, whereas largest decrease was caused by sprawling urban areas.
In 2015, on average, there were around 1.5 fragmented landscape elements per km 2 in the European Union [1] , a 3.7 % increase compared with 2009.
Approximately 1.13 million km 2 , around 28 % of the area of the EU [1] , was strongly fragmented i n 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.
Change of vegetation productivity during the years 2000-2016. Vegetation productivity was calculated for each 500m grid cell from a remote sensing derived vegetation index (PPI). The layer shows the changes expressed in % of 2000 calculated from the fitted line of the linear trend model.
For visualisation purposes, the initial 100 m spatial resolution Corine Land Cover dataset was re-sampled to a 10 km2 grid. The observation periods can be visualised by activating the 'layers' icon and selecting the respective periods.
This web map application uses the new version of the Effective Mesh Density (seff) 2016 dataset with improved input data, for the years 2009, 2012 and 2015. This new dataset uses the Copernicus Imperviousness and the TomTom TeleAtlas data sets as fragmenting geometries. The application shows the change in effective mesh density (seff), i.e. the number of landscape elements between 2009 and 2012 and between 2012 and 2015.
The map shows the density of soil sealing in 2012, based on a 10 km2 reference grid. Green and light orange colors show areas with no or very limited sealing, while red and dark red colors show highly to fully sealed grid cells (mainly urban areas).
The map shows the percentage of the average annual change in soil sealing for each of the rectangular 10 km x 10 km grid cells, over the 2006-2015 period
The chart shows the vegetation productivity changes (%) over areas with land use change in the period 2000-2018. The values are broken down by major land use change drivers.
The chart shows significant trends of vegetation productivity, expressed in % change. The % change values were derived from the fitted linear trend line.
For the reference year 2015 , 85 861 km 2 of the total area covered by the EEA-39 countries were mapped and categorised as 'sealed surface' in the Copernicus imperviousness product. This ...
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