AndreaBozzo/ceres-open-data-index huggingface dataset:
ESA Glaciers Climate Change Initiative (Glaciers CCI): Randolph Glacier Inventory gridded data product, v5.0

The Randolph Glacier Inventory (RGI 5.0) is a global inventory of glacier outlines. It is supplemental to the Global Land Ice Measurements from Space initiative (GLIMS). Production of the RGI was motivated by the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Future updates will be made to the RGI and the GLIMS Glacier Database in parallel during a transition period. As all these data are incorporated into the GLIMS Glacier Database and as download tools are developed to obtain GLIMS data in the RGI data format, the RGI will evolve into a downloadable subset of GLIMS, offering complete one-time coverage, version control, and a standard set of attributes.The product provided here is a converted raster version of the Randolph Glacier Inventory (RGI 5.0) data, provided by the ESA Climate Change Initiative (CCI) Glaciers project.   The CCI Glaciers project is one of a number of contributors to the RGI 5.0 dataset. For more details, and for a complete list of contributors, please see the RGI 5.0 Technical Report in the Documentation section below.The following reference is recommended when citing RGI version 5.0:Arendt, A., A. Bliss, T. Bolch, J.G. Cogley, A.S. Gardner, J.-O. Hagen, R. Hock, M. Huss, G. Kaser, C. Kienholz, W.T. Pfeffer, G. Moholdt, F. Paul, V. RadiÄ, L. Andreassen, S. Bajracharya, N.E. Barrand, M. Beedle, E. Berthier, R. Bhambri, I. Brown, E. Burgess, D. Burgess, F. Cawkwell, T. Chinn, L. Copland, B. Davies, H. De Angelis, E. Dolgova, L. Earl, K. Filbert, R. Forester, A.G. Fountain, H. Frey, B. Giffen, N. Glasser, W.Q. Guo, S. Gurney, W. Hagg, D. Hall, U.K. Haritashya, G. Hartmann, C. Helm, S. Herreid, I. Howat, G. Kapustin, T. Khromova, M. KÃ¶nig, J. Kohler, D. Kriegel, S. Kutuzov, I. Lavrentiev, R. LeBris, S.Y. Liu, J. Lund, W. Manley, R. Marti, C. Mayer, E.S. Miles, X. Li, B. Menounos, A. Mercer, N. MÃ¶lg, P. Mool, G. Nosenko, A. Negrete, T. Nuimura, C. Nuth, R. Pettersson, A. Racoviteanu, R. Ranzi, P. Rastner, F. Rau, B. Raup, J. Rich, H. Rott, A. Sakai, C. Schneider, Y. Seliverstov, M. Sharp, O. SigurÃ°sson, C. Stokes, R.G. Way, R. Wheate, S. Winsvold, G. Wolken, F. Wyatt, N. Zheltyhina, 2015, Randolph Glacier Inventory â A Dataset of Global Glacier Outlines: Version 5.0. Global Land Ice Measurements from Space, Boulder Colorado, USA. Digital Media.
ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Monthly climatology of global ocean colour data products at 4km resolution, Version 6.0

The ESA Ocean Colour CCI project has produced global, level 3, binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.This dataset contains a monthly climatology of the generated ocean colour products covering the period 1997 - 2022.Data products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.
ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Obs4MIPS monthly-averaged sea surface temperature data, v2.1

This dataset contains monthly 1 degree averages of sea surface temperature data in Obs4MIPS format, from the European Space Agency (ESA)'s Climate Change Initiatve (CCI) Sea Surface Temperature (SST) v2.1 analysis.The data covers the period from 1981-2017, with the data from 1981 to 2016 coming from the Sea Surface Temperature (SST) project of the ESA CCI project. The data for 2017 were generated using the same approach but under funding from the Copernicus Climate Change Service (C3S).This particular product has been generated for inclusion in Obs4MIPs (Observations for Model Intercomparisons Project), which is an activity to make observational products more accessible for climate model intercomparisons.Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/When citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x
ESA Sea Level Climate Change Initiative (Sea_Level_cci): Regional coastline profile of Vertical Land Motions in Europe and SE Asia/Oceania,  v1

This dataset contains a regional coastline profile of Vertical Land Motions in Europe and SE Asia/Oceania  produced as part of the ESA Climate Change Initiative Sea Level project.Vertical Land Motions have been estimated as the difference between the altimeter coastal sea level v1.1 dataset (available from https://catalogue.ceda.ac.uk/uuid/222cf11f49a94d2da8a6da239df2efc4 ) and tide gauge measurements from the Permanent Service for Mean Sea Level (PMSML) network. Spatial interpolation has allowed the production of a regularly spaced coastline profile of vertical land movements together with their uncertainties.The altimeter input data are from the Jason-1, Jason-2 and Jason-3 missions during the period Jan. 2002 - May 2018.
ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Nimbus-5 ESMR Sea Ice Concentration, version 1.1

This dataset provides Sea Ice Concentration (SIC) for the polar regions, derived from the Nimbus-5 Electrical Scanning Microwave Radiometer (ESMR), which operated between 1972 and 1977. It is processed with an algorithm using the single channel ESMR data (19.35 GHz), and has been gridded at 25 km grid spacing. This is the second version of the product, v1.1.This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.
ESA Water Vapour Climate Change Initiative (Water_Vapour_cci): Total Column Water Vapour daily gridded data over land at 0.05 degree resolution, version 3.2

This dataset consists of daily total column water vapour (TCWV) over land, at a 0.05 degree resolution, observed by various satellite instruments.   It has been produced by the European Space Agency Water Vapour Climate Change Initiative (Water_Vapour_cci), and forms part of their TCVW over land Climate Data Record -1  (TCWV-land (CDR-1).This version of the data is v3.2.  This is an updated dataset, which fixes an issue with the filtering of the v3.1 data.
GOME Total Column Water Vapour Climate product

The GOME Total Column Water Vapour (TCWV) Climate product was generated by the Max Planck Institute for Chemistry (MPIC), and the German Aerospace Center (DLR) within the ESA GOME-Evolution project. It is a Level 3 type product containing homogenized time-series of the global distribution of TCWV spanning over more than two decades (1995-2015).  The data is provided as single netCDF file, containing monthly mean TCWV (units kg/m2) with 1-degree resolution, and is based on measurements from the satellite instruments ERS-2 GOME, Envisat SCIAMACHY, and MetOp-A GOME-2.  Details are available in the paper by Beirle et al, 2018,.  Please also consult the GOME TCWV Product Quality Readme file before using the data. (https://earth.esa.int/eogateway/documents/20142/37627/GOME-TCWV-Product-sQuality-Readme-File.pdf)
ADAM Surface Reflectance Database v4.0

ADAM enables generating typical monthly variations of the global Earth surface reflectance at 0.1° spatial resolution (Plate Carree projection) and over the spectral range 240-4000nm.  The ADAM product is made of gridded monthly mean climatologies over land and ocean surfaces, and of a companion API toolkit that enables the calculation of hyperspectral (at 1 nm resolution over the whole 240-4000 nm spectral range) and multidirectional reflectances (i.e. in any illumination/viewing geometry) depending on user choices.  The ADAM climatologies that feed the ADAM calculation tools are:  For ocean:  monthly chlorophyll concentration derived from SeaWiFS-OrbView-2 (1999-2009); it is used to compute the water column reflectance (which shows large spectral variations in the visible, but is insignificant in the near and mid infrared). monthly wind speed derived from SeaWinds-QuikSCAT-(1999-2009); it is used to calculate the ocean glint reflectance. For land:  monthly normalized surface reflectances in the 7 MODIS narrow spectral bands derived from FondsdeSol processing chain of MOD09A1 products (derived from Aqua and Terra observations), on which relies the modelling of the hyperspectral/multidirectional surface (soil/vegetation/snow) reflectance. uncertainty variance-covariance matrix for the 7 spectral bands associated to the normalized surface reflectance. For sea-ice:  Sea ice pixels (masked in the original MOD09A1 products) have been accounted for by a gap-filling approach relying on the spatial-temporal distribution of sea ice coverage provided by the CryoClim climatology for year 2005.
EarthCARE L1 Products for Cal/Val Users

This EarthCARE collection is restricted, and contains the following data products:

· Level 1b: Fully Calibrated and Geolocated Instrument Science Measurements

Level 1b data represents the fully processed, calibrated, and geolocated measurements from EarthCARE's instruments. Each measurement is aligned with the native instrument grid. For the Broadband Radiometer (BBR), measurements are also spatially integrated to various groundpixel sizes.

· Level 1c (MSI only): MSI Level 1b Data Interpolated to a Common Spatial Grid

Specifically for the Multi-Spectral Imager (MSI), Level 1c data involves interpolating Level 1b measurements onto a standardized spatial grid that is consistent across all MSI bands. This grid closely matches the spacing used in MSI Level 1b data.

· Level 1d: Joint Standard Grid (JSG) for All Instruments with ECMWF Meteorological Fields.

Level 1d data provides a spatial grid to enable easy collocation and synergistic use of the data from all EarthCARE instruments, named the "joint standard grid." Additionally, this level incorporates ECMWF (European Centre for Medium-Range Weather Forecasts) meteorological fields limited to the EarthCARE swath, enabling comprehensive analysis and modeling of atmospheric conditions within the satellite's coverage area.
EarthCARE ESA L2 Products for Cal/Val Users

This EarthCARE collection is restricted, and contains the following data products:

· Level 2a: Single-Instrument Geophysical Products

These products are derived from individual instrument data onboard EarthCARE. They provide detailed geophysical parameters and properties specific to each instrument's capabilities for example cloud and aerosol properties derived solely from radar or lidar measurements, offering high-resolution insights into atmospheric phenomena.

· Level 2b: Synergistic Geophysical Products

Level 2b products leverage data from multiple EarthCARE instruments to generate comprehensive, synergistic geophysical datasets. By combining measurements from instruments like radar, lidar, and radiometers, these products offer a more integrated view of cloud-aerosol interactions and atmospheric dynamics. Synergistic products provide enhanced accuracy and depth compared to single-instrument outputs, enabling detailed studies of complex atmospheric processes.
AVHRR Level-1B Local Area Coverage Imagery

This collection is composed of AVHRR L1B products (1.1 km) reprocessed from the NOAA POES and Metop AVHRR sensors data acquired at the University of Dundee and University of Bern ground stations and from the ESA and University of Bern data historical archive. The product format is the NOAA AVHRR Level 1B that combines the AVHRR data from the HRPT stream with ancillary information like Earth location and calibration data which can be applied by the user. Other appended parameters are time codes, quality indicators, solar and satellite angles and telemetry. Two data collections cover the Europe and the neighbouring regions in the period of 1 January 1981 to 31 December 2020 and the acquired data in the context of the 1-KM project in the ‘90s. During the early 1990’s various groups, including the International Geosphere-Biosphere Programme (IGBP), the Commission of the European Communities (CEC), the Moderate Resolution Imaging Spectrometer (MODIS) Science Team and ESA concluded that a global land 1-KM AVHRR data set would have been crucial to study and develop algorithms for several land products for the Earth Observing System.   USGS, NOAA, ESA and other non-U.S. AVHRR receiving stations endorsed the initiative to collect a global land 1-km multi-temporal AVHRR data set over all land surfaces using NOAA's TIROS "afternoon" polar-orbiting satellite. On the 1st of April 1992, the project officially began up to the end of 1999 with the utilisation of 23 stations worldwide plus the NOAA local area coverage (LAC) on-board recorders. The global land 1-km AVHRR dataset is composed of 5 channels, raw AVHRR dataset at 1.1km resolution from the NOAA-11 and NOAA-14 satellites covering land surfaces, inland water and coastal areas. Spatial coverage: Check the spatial coverage of the collection on a map available on the Third Party Missions Dissemination Service: _$$AVHRR L1B 1.1 KM$$ https://tpm-ds.eo.esa.int/socat/AVHRR_L1B_1_1KM _$$AVHRR L1B LAC Out-of-Europe$$ https://tpm-ds.eo.esa.int/socat/NOAA_AVHRR_L1B_LAC_out-of-Europe
Sentinel-1 Level-1 Ground Range Detected (GRD) SIGMA0 products.

The Sigma0 product describes how much of the radar signal that was sent out by Sentinel-1 is reflected back to the sensor, and depends on the characteristics of the surface. This product is derived from the L1-GRD product. Typical SAR data processing, which produces level 1 images such as L1-GRD product, does not include radiometric corrections and significant radiometric bias remains. Therefore, it is necessary to apply the radiometric correction to SAR images so that the pixel values of the SAR images truly represent the radar backscatter of the reflecting surface. The radiometric correction is also necessary for the comparison of SAR images acquired with different sensors, or acquired from the same sensor but at different times, in different modes, or processed by different processors. For this Sigma0 product, radiometric calibration was performed using a specific Look Up Table (LUT) that is provided with each original GRD product. This LUT applies a range-dependent gain including the absolute calibration constant, in addition to a constant offset. Next to calibration, also orbit correction, border noise removal, thermal noise removal, and range doppler terrain correction steps were applied during production of Sigma0. The terrain correction step is intended to compensate for distortions due to topographical variations of the scene and the tilt of the satellite sensor, so that the geometric representation of the image will be as close as possible to the real world.
PROBA-V L2A 100M ANTARCTICA COG: 100M projected segment data covering Antarctica, COG format - Collection 1

The product original source is the PROBA-V mission and has been produced by VITO, see https://doi.org/10.5270/PRV-2vvxhtt.A Level2A product contains the projected Level1C data, i.e. radiometrically and geometrically corrected TOA reflectance values projected on a uniform grid, given per band/camera. The applied coordinate reference system is the âGeographic Lat/Lonâ (EPSG:4326)  projection with a spatial resolution of 100 m.
ESA WorldCover 10 meter Land Cover Map 2020

The ESA WorldCover product is a global land cover map with 11 land cover classes. WorldCover provides worldwide coverage at 10 meters and is provided per 3 x 3 degree tile. Note that ocean areas and inner ice sheets do not have tiles. Data is provided as Cloud Optimized GeoTIFFs. The ESA WorldCover product has been produced by a consortium lead by VITO (Belgium) together with Brockmann Consult (Germany), CS SI (France), Gamma Remote Sensing AG (Switzerland), International Institute for Applied Systems Analysis (Austria) and Wageningen University (The Netherlands).				Naming convention: ESA_WorldCover_10m_[YEAR]_[VERSION]_[TILE]_[LAYER].tif/ 				* [YEAR] indicates the reference year (observation period) in four digits.				* [VERSION] shows the product version. The version denoted as vMmr (e.g. v201), with âMâ representing the major version (e.g. v2), âmâ the minor version (starting from 0) and ârâ the production run number (starting from 1) 				* [TILE] the designation of the 3 x 3 degree tile, composed of the 2-digit latitude and 3-digit longitude of the lower-left corner. Example:  N19W100  for the tile covering the area from 100W to 99W and 19N to 20N.				For example: ESA_WorldCover_10m_2020_v100_N19W100_Map.tif/
Sentinel-3 Level 3 Land Surface Temperature daily synthesis product - V1

The Sentinel-3, Level 3 Land Surface Temperature S1 products (S3_LST_3_S1) contain 1 km daily LST composites. TMeasurements are provided on a regular latitude-longitude grid, with an equatorial sampling distance of approximately 1 km (1Â° / 112). The LST and LST_unc are provided, derived from unflagged S3_SL_2_LST inputs at minimum viewing zenith angle.
ESA WorldCover 10 meter Land Cover Map 2021

The ESA WorldCover product is a global land cover map with 11 land cover classes. WorldCover provides worldwide coverage at 10 meters and is provided per 3 x 3 degree tile. Note that ocean areas and inner ice sheets do not have tiles. Data is provided as Cloud Optimized GeoTIFFs. The ESA WorldCover product has been produced by a consortium lead by VITO (Belgium) together with Brockmann Consult (Germany), CS SI (France), Gamma Remote Sensing AG (Switzerland), International Institute for Applied Systems Analysis (Austria) and Wageningen University (The Netherlands).				Naming convention: ESA_WorldCover_10m_[YEAR]_[VERSION]_[TILE]_[LAYER].tif/ 				* [YEAR] indicates the reference year (observation period) in four digits.				* [VERSION] shows the product version. The version denoted as vMmr (e.g. v201), with âMâ representing the major version (e.g. v2), âmâ the minor version (starting from 0) and ârâ the production run number (starting from 1) 				* [TILE] the designation of the 3 x 3 degree tile, composed of the 2-digit latitude and 3-digit longitude of the lower-left corner. Example:  N19W100  for the tile covering the area from 100W to 99W and 19N to 20N.				For example: ESA_WorldCover_10m_2021_v200_N19W100_Map.tif/
ESA WorldCereal products for active cropland per agro-ecological zone - V1

The WorldCereal active cropland products provide binary maps for all growing seasons as defined by the WorldCereal global crop calendars, showing where active cropland has been detected. Seasonal active cropland is defined by the WorldCereal system as actively cultivated cropland during a specific growing season. In order for a pixel to be labeled as active during a particular growing season, a full crop growth cycle (sowing, growing, senescence and harvesting) needs to take place within the designated time period. Note that this active marker is not crop-type specific and only consider specific seasonality. This also means in practice that any crop grown (slightly) outside the predefined growing seasons will not be flagged as active cropland in any of the seasons covered by these products. The WorldCereal active cropland products were generated within the respective annual temporary crops mask.
MapEO Water Chlorophyll-a (CHL) Products - V1

Optical data collected with airborne drone platform, and processed with MapEO Water software v1 at VITO into chlorophyll-a concentrations. Chlorophyll-a is a green pigment found in plants. It absorbs sunlight and converts it into sugar during photosynthesis. Chlorophyll-a concentrations are an indicator of phytoplankton abundance and biomass in inland, coastal, and estuarine waters. CHL is expressed in Î¼g L-1 or mg m-3.
PROBA-V L2A 1KM HDF: 1KM projected segment data, HDF format - Collection 2

A Level2A product contains the projected Level1C (Pâproduct) data, i.e. radiometrically and geometrically corrected TOA reflectance values projected on a uniform grid, given per band/camera. The applied coordinate reference system is the âGeographic Lat/Lonâ (EPSG:4326)  projection with a spatial resolution of 1 km.
PROBA-V S5 NDVI TOC 100 m HDF: Data corrected for atmospheric effects with the SMAC (Simplified Method for Atmosheric Corrections) algorithm, HDF format - Collection 2

Level 3 data products are variables mapped on uniform space-time grid scales and are the result of combining multiple scenes (e.g. S1/S5/S10) to cover the userâs region of interest.
PROBA-V S5 NDVI TOC 100 m COG: Data corrected for atmospheric effects with the SMAC (Simplified Method for Atmosheric Corrections) algorithm, COG format - Collection 2

Level 3 data products are variables mapped on uniform space-time grid scales and are the result of combining multiple scenes (e.g. S1/S5/S10) to cover the userâs region of interest.
GCOM-C/SGLI L2 Statistics-Land Surface Reflectance(RV04) (1-Month,250m)

GCOM-C/SGLI L2 Statistics-Land Surface Reflectance (RV04) (1-Month, 250m) is obtained from the SGLI sensor onboard GCOM-C and produced by the Japan Aerospace Exploration Agency (JAXA). Using the Level 2 atmospheric corrected land surface reflectance tile product as input, BRDF correction is performed for the land surface in clear region using data of multiple days, and the reflectance equivalent to that at nadir view direction is stored in the output product. The region definition and spatial resolutions of the output product are kept the input data. In 1-Month processing, the land surface reflectance data of the past 1 month, respectively are fitted to generate appropriate BRDF models with the correction coefficients. GCOM-C is Sun-synchronous sub-recurrent Orbit satellite launched on December 23, 2017, which mounts SGLI and conducts long-term global observations of geophysical variables related to the global climate system across 28 items including aerosol and vegetation over 4 areas of atmosphere, land, ocean, and cryosphere. The data will be used to contribute to higher accuracy of global warming prediction. The SGLI has swath of 1150 km in the visible band and 1400 km in the infrared band.This dataset includes of following SDs (Center Wavelength is correspond to channel name as same as L1B):  Rs_VN04_AVE is Average surface reflectance [unit: none] Rs_VN04_Date is Date identification of surface reflectance [unit: none] Rs_VN04_MAX is Maximum of surface reflectance [unit: none] Rs_VN04_MIN is Minimum of surface reflectance [unit: none] Rs_VN04_Ninput is Input data number of surface reflectance [unit: none] Rs_VN04_Nused is Used data number of surface reflectance [unit: none] Rs_VN04_QA_flag is quality flag about the statistics and BRDF regression [unit: none] Rs_VN04_RMS is root-mean-square (RMS) of BRDF model regression of surface reflectance [unit: none] Rs_VN04_c0-2 are c0, c1, and c2 coefficients of surface reflectance [unit: none] The provided format is HDF5. The spatial resolution is 250 m. The statistical period is 1 month also 8 days statistics is available. The projection method is EQA. The generation unit is Tile. The current version of the product is Version 3. The Version 2 is also available.