Several layers describing density of surface water / streams projected to the Good Homolosine projection. List of layers included: hyd_log1p.upstream.area_merit.hydro_m = Upstream Drainage Area based on the MERIT Hydro, hyd_river.density_gloric_p = rasterized Global River Classification (GLORIC) DB, lcv_water.occurance_jrc.surfacewater_p = Surface Water based on the JRC's Global Surface Water, lcv_water.seasonal_probav.glc.lc100_p = Seasonal Inland Water probability based on the Copernicus LC100 map, lcv_wetlands.cw_upmc.wtd_c = composite wetland (CW) map based on Tootchi et al. (2019), Goode_Homolosine_domain_250m.tif = map domain prepared by Luís de Sousa, tiles_GH_100km_land.gpkg = 100 km x 100 km tiling system covering the land mass, Important notes: Processing steps are described in detail here. Antartica is not included. Reprojecting maps to Goode Homolosine projection can be cumbersome and small amount of artifacts at the edges of the map can be anticipated. These maps were develop in connection to the OpenLandMap.org initiative. If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some of the following channels: Technical issues and questions about the code: https://gitlab.com/openlandmap/global-layers/issues General questions and comments: https://disqus.com/home/forums/landgis/ All files internally compressed using "COMPRESS=DEFLATE" creation option in GDAL. File naming convention: hyd = theme: hydrology and water dynamics, log1p.upstream.area = variable: log(X+1)*10 of the upstream area, merit.hydro = determination method: MERIT Hydro, m = mean value, 250m = spatial resolution / block support: 250 m, b0..0cm = vertical reference: surface, 2017 = time reference: period 2017, v0.1 = version number: 0.1,

{"references": ["Pekel, J. F., Cottam, A., Gorelick, N., & Belward, A. S. (2016). High-resolution mapping of global surface water and its long-term changes. Nature, 540(7633), 418.", "Ouellet Dallaire, C., Lehner, B., Sayre, R., Thieme, M. (2018): A multidisciplinary framework to derive global river reach classifications at high spatial resolution. Environmental Research Letters. doi: 10.1088/1748-9326/aad8e9", "Tootchi, A., Jost, A., and Ducharne, A. (2019): Multi-source global wetland maps combining surface water imagery and groundwater constraints, Earth Syst. Sci. Data, 11, 189-220, https://doi.org/10.5194/essd-11-189-2019", "Underwood, E. (2019): A more accurate global river map, Eos, 100, https://doi.org/10.1029/2019EO128033", "Yamazaki D., D. Ikeshima, J. Sosa, P.D. Bates, G.H. Allen, T.M. Pavelsky, (2019): MERIT Hydro: A high-resolution global hydrography map based on latest topography datasets Water Resources Research, ACCEPTED, https://doi.org/10.1029/2019WR024873"]}