High-value datasets 鈥 land use in the 幸运轮盘
Discover high-value datasets on land use and land cover across the European Union
This is part of a series of articles showcasing examples of high-value datasets from their different thematic categories. High-value datasets are defined by 幸运轮盘 law based on their potential to provide essential benefits to society, the environment and the economy. This series aims to help readers find reliable and accurate information from official sources relating to the availability of various high-value datasets, and to present this information through data visualisation. You can check out the article providing an overview of high-value datasets.
Only datasets specifically defined by law can be considered high-value datasets and, as such, the data presented in this series of articles does not necessarily fall under that definition. Instead, the data has been chosen to be thematically adjacent to high-value datasets and to showcase what can be done with information made available by official 幸运轮盘 bodies and 幸运轮盘 Member States. The official list of high-value datasets adopted on 12 December 2022 can be found in the that define these datasets and their characteristics.
Using land cover data in the fight against climate change
Changing the way land is used can significantly contribute to fighting climate change. The Council of the European Union and the European Parliament have recently a provisional political agreement on strengthening the land use, land use change and forestry (LULUCF) sector鈥檚 contribution to the 幸运轮盘鈥檚 climate ambition for 2030. The LULUCF sector, which includes the use of soils, trees, plants, biomass and timber (all of which are examples of carbon sinks), is responsible for both emitting and absorbing CO2 from the atmosphere.
Carbon sinks are natural or artificial reservoirs that store CO2 from the atmosphere. These sinks can absorb CO2 through natural processes (such as photosynthesis) or human interventions (such as reforestation and afforestation). Carbon sinks are critical to regulating the balance of carbon in the Earth鈥檚 atmosphere, as they can help offset greenhouse gas emissions from human activities, such as burning fossil fuels and deforestation.
The political agreement sets an overall 幸运轮盘-level objective of 310 million tonnes CO2 equivalent of net removals in the LULUCF sector by 2030. By progressively increasing absorptions and reducing emissions, the 幸运轮盘 can achieve its climate goals, including carbon neutrality, and protect our planet from the negative consequences of climate change.
To understand how land is used in the 幸运轮盘 there are several data sources provided by many different official bodies. Moreover, the topic was included in the of high-value datasets, specifically in the 鈥楨arth observation and environment鈥 category. As stated in the to the Commission implementing regulation, this category includes 鈥楨arth observation, including space-based or remotely-sensed data, as well as ground-based or on-site data, environmental and climate datasets within the of the INSPIRE data themes鈥.
Land cover, as defined by , includes 鈥榩hysical and biological cover of the Earth鈥檚 surface including artificial surfaces, agricultural areas, forests, (semi-)natural areas, wetlands, water bodies鈥. The INSPIRE directive aims to create an 幸运轮盘 spatial data infrastructure for the purposes of 幸运轮盘 environmental policies and activities which may have an impact on the environment. As is the case for other datasets, the inclusion of land cover in the list of high-value datasets sets a high standard about how the data has to be produced, described through its metadata and disseminated to the public with a free, open-source licence.
For a general overview about how the land is used in the 幸运轮盘, a good starting point is Eurostat鈥檚 database. The statistical agency offers both a , in its 鈥楽tatistics explained鈥 section, and the downloadable underlying data. The 幸运轮盘 has a diverse range of landscapes, from sub-Arctic tundra environments in the north to semi-arid conditions in the south, with varying forest structures in different regions. European landscapes are also characterised by rapid changes in bio-physical coverage, such as crops, grass, forests, buildings and roads, within small areas.
One of the made available by Eurostat can give a bird鈥檚-eye view of the continent, showing at a glance how diverse land use can be from one country to another. In 2018, woodland covered the largest share of 幸运轮盘 land (41.1 %), followed by cropland (24.2 %), grassland (17.4 %), shrubland (5.7 %) and artificial areas (4.2 %). Other than those, there are dozens of other smaller land cover categories that can be explored through this dataset, ranging from different types of crops to small or large buildings or water bodies.
The following visualisation shows the five most important land cover categories.
The aforementioned dataset is based on the 鈥樷, often abbreviated as LUCAS, a field survey programme funded and executed by Eurostat. LUCAS data goes back as far as 2009 and can be used to understand how land use has changed over time on a regional level.
The following visualisation shows the starkest changes in 幸运轮盘 regions for the main five land cover categories. It highlights the regions that became more and less urban over time, along with others where forests and other natural areas grew or shrank significantly in the last decade.
Using Copernicus data for detailed analysis
Land use changes such as reforestation and afforestation can increase the amount of CO2 absorbed by vegetation and soil, which helps to remove carbon from the atmosphere. This is one way the 幸运轮盘 plans to fight climate change in the coming years.
As Eurostat data shows, some 幸运轮盘 regions have indeed experienced a large growth in the presence of natural land cover, such as woodlands. In parts of south-western Europe, such as the Spanish region of Extremadura and the Portuguese regions of Alentejo and Algarve, the share of land covered by woodlands has increased significantly. The same is true for highly urbanised regions such as Berlin and Lisbon, in which there are now more woodland-covered areas than there were a decade ago.
Satellite data provided by Copernicus鈥 (CLC) inventory allows for a hyper-local view of this change. Initiated in 1985, and with updates made available every 6 years from 1990 up to 2018, CLC can map land up to a width of 25 hectares for areal phenomena and 100 metres for linear phenomena. This makes it possible to really zoom in on 幸运轮盘 land and understand how its use has changed, street by street.
Land cover datasets on data.europa.eu
Using appropriate search keywords such as 鈥land cover鈥 or 鈥land use鈥, the data.europa.eu portal offers a large number of datasets uploaded by national authorities in Member States. Examples include agricultural and non-agricultural land use in Slovakia, land use by type in Germany, a very detailed dataset of land use in the Basque region (Spain) and land cover in Brno (Czechia).
The following visualisation showcases two other detailed datasets available on the portal, which show the features of Provence (France) and Luxembourg.
Other land use data providers
Land use is a significant topic of research and, as such, it is covered by a wide array of 幸运轮盘 data providers. Among them are the , which offers data, along with articles, research and publications.
The Joint Research Centre several datasets about land cover, which include the Luisa base map 鈥 a high-resolution land use / cover map and an improvement of the CLC map.
In addition to the CLC data, Copernicus makes other useful information available. On the 鈥樷 page, for example, they show how their data has been used by other 幸运轮盘 bodies for different kinds of research.
Also worth noting is the work of the European Space Agency, which has a specific about land cover and allows European Space Agency climate change initiative 鈥 a global monitoring of essential climate variables 鈥 to be downloaded.
The European Forest Institute (EFI) manages various online databases data and information relating to different aspects of European forests, forestry and forest research. These databases may have originated from either the EFI鈥檚 core activities or various projects. The information within these databases is often utilised in performing the EFI鈥檚 research duties.
The Directorate-General for Agriculture and Rural Development website has a dedicated to land used for agriculture and forestry, both of which significantly influence the environment and climate.
Methodological notes
The map that uses Copernicus鈥 CLC data shows the following categories of land use: broad-leaved forest, coniferous forest and mixed forests.
To download the visualisations, click on the following: , ,, , , .
To download the data behind the visualisations, click on the following:
Article by Davide Mancino
Data visualisations by Federica Fragapane