Region of Interest (ROI) is comprised of the Belgium, the Netherlands and Luxembourg We use the communes adminitrative division which is standardized across Europe by EUROSTAT at: https://ec.europa.eu/eurostat/web/gisco/geodata/reference-data/administrative-units-statistical-units This is roughly equivalent to the notion municipalities in most countries. From the link above, communes definition are taken from COMM_RG_01M_2016_4326.shp and country borders are taken from NUTS_RG_01M_2021_3035.shp. images: Sentinel2 RGB from 2020-01-01 to 2020-31-12 filtered out pixels with clouds acoording to QA60 band following the example given in GEE dataset info page at: see https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S2_SR_HARMONIZED see also https://github.com/rramosp/geetiles/blob/main/geetiles/defs/sentinel2rgbmedian2020.py labels: Global Human Settlement Layers, Population Grid 2015 labels range from 0 to 31, with the following meaning: label value original value in GEE dataset 0 0 1 1-10 2 11-20 3 21-30 ... 31 >=291 see https://developers.google.com/earth-engine/datasets/catalog/JRC_GHSL_P2016_POP_GPW_GLOBE_V1 see also https://github.com/rramosp/geetiles/blob/main/geetiles/defs/humanpop2015.py _aschips.geojson the image chips geometries along with label proportions for easy visualization with QGIS, GeoPandas, etc. _communes.geojson the communes geometries with their label prortions for easy visualization with QGIS, GeoPandas, etc. splits.csv contains two splits of image chips in train, test, val - with geographical bands at 45° angles in nw-se direction - the same as above reorganized to that all chips within the same commune fall within the same split. data/ a pickle file for each image chip containing a dict with - the 100x100 RGB sentinel 2 chip image - the 100x100 chip level lavels - the label proportions of the chip - the aggregated label proportions of the commune the chip belongs to