Advances in LUCAS Copernicus 2022: enhancing Earth observations with comprehensive in situ data on EU land cover and use
| Autor: | R. d'Andrimont, M. Yordanov, F. Sedano, A. Verhegghen, P. Strobl, S. Zachariadis, F. Camilleri, A. Palmieri, B. Eiselt, J. M. Rubio Iglesias, M. van der Velde |
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| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Earth System Science Data, Vol 16, Pp 5723-5735 (2024) |
| Druh dokumentu: | article |
| ISSN: | 5723-2024 1866-3508 1866-3516 |
| DOI: | 10.5194/essd-16-5723-2024 |
| Popis: | The Land Use/Cover Area frame Survey (LUCAS) of the European Union (EU) presents a rich resource for detailed understanding of land cover and use, making it invaluable for Earth observation (EO) applications. This paper discusses the recent enhancements and improvements in the LUCAS Copernicus module, particularly the data collection process of 2022, its protocol simplifications, and geometry definitions compared to the 2018 survey and data. With approximately 150 000 polygons collected in 2022, an increase from 60 000 in 2018, the LUCAS Copernicus 2022 data provide a unique and comprehensive in situ dataset for EO applications. The protocol simplification also facilitates a faster and more efficient data collection process. In 2022, there were 137 966 polygons generated out of the original 149 408 LUCAS Copernicus points, which means that 92.3 % of the points were actually surveyed. The data have 82 land cover classes for the Copernicus module that map to 88 classes up to the LUCAS level-3 legend. For land use the data have 40 classes, along with 18 classes of land use types. The dataset is available for download (product IDentification – PID: http://data.europa.eu/89h/e3fe3cd0-44db-470e-8769-172a8b9e8874; European Commission, 2023). The paper elaborates further on the implications of these enhancements and the need for continuous harmonization to ensure semantic consistency and temporal usability of data across different periods. Moreover, it calls for additional studies exploring the potential of the collected data, especially in the context of remote sensing and computer vision. It ends with a discussion of future data usage and dissemination strategies. |
| Databáze: | Directory of Open Access Journals |
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