AndreaBozzo/ceres-open-data-index huggingface dataset:
Global WaterPack - MODIS - Yearly

The Global WaterPack is a dataset containing information about open surface water cover parameters on a global scale. The water detection is derived from daily, operational MODIS datasets for every year since 2003. The negative effects of polar darkness and cloud coverage are compensated by applying interpolation processing steps. Thereby, a unique global dataset can be provided that is characterized by its high temporal resolution of one day and a spatial resolution of 250 meter. Furthermore, reliability and observation layers provide additional information on the quality of each Global WaterPack pixel at daily, monthly, and yearly temporal scale.
TanDEM-X - Digital Elevation Model (DEM) - Global, 90m

TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements) is an Earth observation radar mission that consists of a SAR interferometer built by two almost identical satellites flying in close formation. With a typical separation between the satellites of 120m to 500m a global Digital Elevation Model (DEM) has been generated.The TanDEM-X 90m DEM is a product variant of the global Digital Elevation Model (DEM) acquired in the frame of the German TanDEM-X mission between 2010 and 2015, and has a reduced pixel spacing of 3 arcseconds (90m at the equator). It covers all Earth’s landmasses from pole to pole.
TanDEM-X Forest/Non-Forest Map - Global

The TanDEM-X Forest/Non-Forest Map is a project developed by the Microwaves and Radar Institute at the German Aerospace Center (DLR), within the activities of the TanDEM-X mission. The goal is the derivation of a global forest/non-forest classification mosaic from TanDEM-X bistatic interferometric synthetic aperture radar (InSAR) data, acquired for the generation of the global digital elevation model (DEM) in Stripmap single polarization (HH) mode.
World Settlement Footprint (WSF) 3D - Material Stock

Buildings provide indispensable services for human wellbeing, but their construction and use are responsible for a substantial fraction of societies’ resource requirements and greenhouse gas emissions. Mapping and quantifying the material stocks in buildings is a key research frontier in Industrial Ecology. Reliable and spatially highly resolved maps of material stocks in buildings world-wide are so far not available. Existing approaches based on nighttime light data allow large-scale coverage, but their spatial resolution is usually ~0.5-1 km. Other methods using light detection and ranging (LiDAR) and cadaster data achieve higher resolution and accuracy, but do not allow wall-to-wall mapping of large regions. Based on high-resolution Earth Observation data combined with material intensity factors (kg per m3 of building volume), we here quantify and map material stocks in buildings at the unprecedented resolution of 90 m globally. We distinguish 18 types of materials in five types of buildings. We find that global material stocks in buildings amount to 547 (391-672) Gt, approximately half of total global societal material stocks. We find highly unequal distributions of material stocks in buildings per capita and per unit area of each country. Our results agree well with previous detailed estimates of material stocks in buildings in dedicated regions or individual cities. Improved and harmonized material intensity factors emerge as a key research area for improving the accuracy of material stock maps. Our results are available as data products with high spatial and thematic resolution to facilitate future studies; e.g., of secondary resource potentials.
Noise - Road Traffic Lden (2002/49/EC) - Germany, 2017

his dataset includes a road traffic noise indicator mapped according to the European Noise Directive (2002/49/EC). The indicator, Lden (Day-Evening-Night Level), describes the equivalent sound pressure level of a 24-hour period, with separate values for daytime, evening, and nighttime periods and is commonly used in environmental noise assessments to evaluate the impact of noise sources on human health and well-being. The input data, simulated noise levels provided as shapefiles by the federal states of Germany, were cleansed and harmonized prior rasterizing them to 10 x 10m.
DESIS L2A HSI Products

The DESIS L2A data is analysis-ready-data (ARD) processed to georeferenced bottom of atmosphere reflectance values using the DESIS L2A atmospheric correction processor (correction over land). It provides binned data (4 x) giving a spectral resolution of ~ 10 nm over the visible to near-infrared wavelength range (400 – 1000 nm). The full resolution data (2.55 nm) and all other available processing level (L1B, L1C) are available at the EOWEB platform (https://eoweb.dlr.de/egp/). The complete data take consists of the Spectral Image, Metadata with information about the spectral response function, center wavelength and flags about pixel quality, two image layers with the information about the Data Quality per pixel and a quicklook image (Overview). It is strongly recommended to download all assets as package for each data take.
Degree of Urbanization - Germany

The degree of urbanization provides urbanization level information at 100x100 meter grids for Germany. It is based on population numbers, building density and the share of building types. It is provided as a continuous percentage value representing the probability of the degree of urbanization, as well as five discrete values representing classes of the degree of urbanization: definitely ‘urban’, probably ‘urban’, area of uncertainty, probably ‘rural’, definitely ‘rural’.
S5P Tropomi L3 P1D SO2 v1

S5P TROPOMI L3 Data of radiometric_cloud_fraction variable. IMPORTANT: This STAC Collection is OUTDATED and has been superseded by a newer version (S5P_TROPOMI_L3_P1D_SO2_v2) following comprehensive data reprocessing. While the STAC metadata for this Collection and its Items remain available for reference and legacy purposes, the underlying data assets are no longer accessible—all asset HREFs will not resolve. Users should migrate to the new Collection for access to current data.
S5P Tropomi L3 P1D O3 v1

S5P TROPOMI L3 Data of radiometric_cloud_fraction variable. IMPORTANT: This STAC Collection is OUTDATED and has been superseded by a newer version (S5P_TROPOMI_L3_P1D_O3_v2) following comprehensive data reprocessing. While the STAC metadata for this Collection and its Items remain available for reference and legacy purposes, the underlying data assets are no longer accessible—all asset HREFs will not resolve. Users should migrate to the new Collection for access to current data.
S5P Tropomi L3 P1D HCHO v1

S5P TROPOMI L3 Data of radiometric_cloud_fraction variable. IMPORTANT: This STAC Collection is OUTDATED and has been superseded by a newer version (S5P_TROPOMI_L3_P1D_HCHO_v2) following comprehensive data reprocessing. While the STAC metadata for this Collection and its Items remain available for reference and legacy purposes, the underlying data assets are no longer accessible—all asset HREFs will not resolve. Users should migrate to the new Collection for access to current data.
Forest Canopy Cover Loss - Germany - Monthly, 10m

This raster dataset shows forest canopy cover loss (FCCL) in Germany at a monthly resolution from September 2017 to October 2025. It is similar to the product developed in Thonfeld et l. (2022) but was fully reprocessed and updated to reveal the most recent forest disturbance dynamics. The combination of Sentinel-2A/B and Landsat-8/9 data allows for a high temporal resolution while the pixel size of the product is 10 m.
S5P Tropomi L3 P1D CTH v1

S5P TROPOMI L3 Data of radiometric_cloud_fraction variable. IMPORTANT: This STAC Collection is OUTDATED and has been superseded by a newer version (S5P_TROPOMI_L3_P1D_CTH_v2) following comprehensive data reprocessing. While the STAC metadata for this Collection and its Items remain available for reference and legacy purposes, the underlying data assets are no longer accessible—all asset HREFs will not resolve. Users should migrate to the new Collection for access to current data.
S5P Tropomi L3 P1D COT v1

S5P TROPOMI L3 Data of radiometric_cloud_fraction variable. IMPORTANT: This STAC Collection is OUTDATED and has been superseded by a newer version (S5P_TROPOMI_L3_P1D_COT_v2) following comprehensive data reprocessing. While the STAC metadata for this Collection and its Items remain available for reference and legacy purposes, the underlying data assets are no longer accessible—all asset HREFs will not resolve. Users should migrate to the new Collection for access to current data.
S5P Tropomi L3 P1D CF v1

S5P TROPOMI L3 Data of radiometric_cloud_fraction variable. IMPORTANT: This STAC Collection is OUTDATED and has been superseded by a newer version (S5P_TROPOMI_L3_P1D_CF_v2) following comprehensive data reprocessing. While the STAC metadata for this Collection and its Items remain available for reference and legacy purposes, the underlying data assets are no longer accessible—all asset HREFs will not resolve. Users should migrate to the new Collection for access to current data.
SoilSuite – Sentinel-2 – Africa, 4 year composite

The SoilSuite contains a collection of different image data products informing about the spectral and statistical characteristics of the African soils. It is generated using DLR's Soil Composite Mapping Processor (ScMAP) that leverages the Sentinel-2 data archive. SCMaP is a specific processing chain for detecting and analyzing bare soil surfaces on a large (continental) scale.
Global WaterPack - MODIS - Daily

The Global WaterPack is a dataset containing information about open surface water cover parameters on a global scale. The water detection is derived from daily, operational MODIS datasets for every year since 2003. The negative effects of polar darkness and cloud coverage are compensated by applying interpolation processing steps. Thereby, a unique global dataset can be provided that is characterized by its high temporal resolution of one day and a spatial resolution of 250 meter. Furthermore, reliability and observation layers provide additional information on the quality of each Global WaterPack pixel at daily, monthly, and yearly temporal scale.
Global WaterPack - MODIS - Monthly

The Global WaterPack is a dataset containing information about open surface water cover parameters on a global scale. The water detection is derived from daily, operational MODIS datasets for every year since 2003. The negative effects of polar darkness and cloud coverage are compensated by applying interpolation processing steps. Thereby, a unique global dataset can be provided that is characterized by its high temporal resolution of one day and a spatial resolution of 250 meter.  Furthermore, reliability and observation layers provide additional information on the quality of each Global WaterPack pixel at daily, monthly, and yearly temporal scale.
SoilSuite – Sentinel-2 – Europe, 5 year composite

The SoilSuite contains a collection of different image data products informing about the spectral and statistical characteristics of the European soils. It is generated using DLR's Soil Composite Mapping Processor (ScMAP) that leverages the Sentinel-2 data archive. SCMaP is a specific processing chain for detecting and analyzing bare soil surfaces on a large (continental) scale.
EnMAP L2A HSI Products

EnMAP L2A HSI Products providing all 224 bands as CEOS-ARD data using athmosperic correction over land (CARD4L). This Collection holds EnMAP L2A HSI Products with 'nominal quality', 'reduced quality' and 'low quality'. Those can be distinguished by using the property 'enmap:overallQuality', here the values respond to {0}: nominal quality, {1}: reduced quality and {2}: low quality.