Articles | Volume 14, issue 10
https://doi.org/10.5194/essd-14-4463-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4463-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
LUCAS cover photos 2006–2018 over the EU: 874 646 spatially distributed geo-tagged close-up photos with land cover and plant species label
Raphaël d'Andrimont
CORRESPONDING AUTHOR
European Commission, Joint Research Centre (JRC), Ispra, Italy
Momchil Yordanov
European Commission, Joint Research Centre (JRC), Ispra, Italy
Laura Martinez-Sanchez
European Commission, Joint Research Centre (JRC), Ispra, Italy
Peter Haub
Imaging Consulting, Altlussheim, Germany
Oliver Buck
EFTAS, EFTAS Fernerkundung Technologietransfer GmbH, Münster, Germany
Carsten Haub
EFTAS, EFTAS Fernerkundung Technologietransfer GmbH, Münster, Germany
Beatrice Eiselt
European Commission, Eurostat (ESTAT), Luxembourg, Luxembourg
Marijn van der Velde
CORRESPONDING AUTHOR
European Commission, Joint Research Centre (JRC), Ispra, Italy
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The Land Use/Cover Area frame Survey (LUCAS) is a regular in situ land cover and land use ground survey exercise that extends over the whole of the European Union. A new LUCAS module specifically tailored to Earth observation was introduced in 2018: the LUCAS Copernicus module. This paper summarizes the LUCAS Copernicus survey and provides the unique resulting data: 58 426 polygons with level-3 land cover (66 specific classes including crop type) and land use (38 classes).
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Short summary
Between 2006 and 2018, 875 661 LUCAS cover (i.e. close-up) photos were taken over a systematic sample of the European Union. This geo-located photo dataset has been curated and is being made available along with the surveyed label data, including land cover and plant species.
Between 2006 and 2018, 875 661 LUCAS cover (i.e. close-up) photos were taken over a systematic...
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