Spatial layers for Europe at 30-m available as Cloud Optimized GeoTiffs
** ** * We have mapped land cover classes for the 2000-2019 period for continental Europe at 30-m resolution using spatiotemporal Machine Learning (we used R and python for modeling). Explore the dynamic EU landscapes on your palm using the ODS-Europe viewer: https://maps.opendatascience.eu * *To access almost 10TB of data using R you use the terra or similar packages e.g.:* **** **R> library(terra)R> in.tif = "/vsicurl/http://s3.eu-central-1.wasabisys.com/eumap/lcv/lcv_landcover.hcl_lucas.corine.rf_p_30m_0..0cm_2019_eumap_epsg3035_v0.1.tif"R> tif = rast(in.tif)** **From here you can use any native operation e.g. to crop some polygon or resample / aggregate values** (there is no need to download whole data sets). A detailed tutorial on how to work with **Cloud Optimized GeoTiffs is available here: https://gitlab.com/openlandmap/global-layers/-/blob/master/tutorial/OpenLandMap_COG_tutorial.md.** Complete list of Cloud Optimized GeoTiffs we produced so far for Europe is available here: https://gitlab.com/geoharmonizer_inea/eumap/-/blob/master/gh_raster_layers.csv ** **If not otherwise specified, the data available on this portal is licensed under the Open Data Commons Open Database License <https://opendatacommons.org/licenses/odbl/> (ODbL) and/or Creative Commons Attribution-ShareAlike 4.0 <https://creativecommons.org/licenses/by-sa/4.0/legalcode> and/or Creative Commons Attribution 4.0 <https://creativecommons.org/licenses/by/4.0/legalcode> International license (CC BY). **** *Read more in: https://opengeohub.medium.com/europe-from-above-space-time-machine-learning-reveals-our-changing-environment-1b05cb7be520 * *If you experience any technical problems or if you discover a bug, please report via: *https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues T. Hengl https://opengeohub.org/about