(NEW) Baltic Sea Region Land Cover Urban (BSRLC-U) focusing on urban built-up types now available: https://zenodo.org/records/17413880 Baltic Sea Region Land Cover Plus (BSRLC+) is annual land cover mapping (30 m) dataset in Europe from 2000 to 2022. The maps contain detailed information of 18 land cover (LC) types, including 9 crop types and 2 peat bog types. Input data : Optical multi-temporal remote sensing imageries (Landsat 5 (TM) / 7 (ETM+) / 8 (OLI) / 9 (OLI+) and Sentinel 2 (A / B ) from 2000 to 2022. Data is processed to surface reflectance and tiled into datacube structure using Framework for Operational Radiometric Correction for Environmental monitoring - FORCE. Mapping method: Maps are produced using data encoding and deep learning classification according to Pham et al. 2024 Validation: Maps have been rigorously validated using independent in-situ data The Land Use/Cover Area frame Survey (LUCAS). Traing data and validation data are available: https://zenodo.org/records/11073291 This dataset contains: 00_preview.png: Preview map (2022) of the Baltic Sea region BSRLC_{year}.tif: Annual map data (30 m) in GeoTIFF format (projection ETRS89 / EPSG:3035) BSRLC_legend.xlss: Land cover codes and class names BSRLC_qgis_style.qml: Map style to be used in QGIS BSRLC_arcgis_style.lyrx: Map style to be used in ArcGIS Land cover codes (can also be found in BSRLC_legend.xlss): 1: Built-up 2: Bareland 3: Water 4: Shrubland 5: Broadleaf forest 6: Coniferous forest 7: Wetland marsh 8: Exploited peat bog 9: Unexploited peat bog 10: Wheat 11: Barley 12: Rye 13: Oat 14: Maize 15: Seed crops 16: Root crops 17: Pulses, vegetable 18: Grassland 255: Nodata Publication (please cite this publication if you are using the dataset): Pham, V.-D., de Waard, F., Thiel, F., Bobertz, B., Hellmann, C., Nguyen, D.-V., Beer, F., Arasumani, M., Schwieder, M., Hartleib, J., Frantz, D., & van der Linden, S. (2024). An annual land cover dataset for the Baltic Sea Region with crop types and peat bogs at 30 m from 2000 to 2022. Scientific Data, 11, 1242, https://doi.org/10.1038/s41597-024-04062-w Other related publications: Pham, V.-D., Tetteh, G., Thiel, F., Erasmi, S., Schwieder, M., Frantz, D., & van der Linden, S. (2024). Temporally transferable crop mapping with temporal encoding and deep learning augmentations. International Journal of Applied Earth Observation and Geoinformation, 129, 103867, https://doi.org/10.1016/j.jag.2024.103867 Frantz, D. (2019). FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sensing, 11, https://doi.org/10.3390/rs11091124 Funding This datatset is created in the frame of the Interdisciplinary Research Center for the Baltic Sea Region Research (IFZO) of University of Greifswald, Germany, and the research project Fragmented Transformations, which is funded by the German Federal Ministry of Education and Research (FKZ 01UC2102).