AndreaBozzo/ceres-open-data-index huggingface dataset:
Standardised Precipitation-Evapotranspiration Index - ERA5_QM SPEI-3

The Standardized Precipitation-Evapotranspiration Index (SPEI) represents a standardized measure of what a certain value of surface water balance (precipitation minus potential evapotranspiration) over the selected time period means in relation to expected value of surface water balance for this period. SPEI is calculated on different time scales (1, 2, 3, 6, 12 months). The value of the SPEI index around 0 represents the normal expected conditions for the surface water balance in the selected period based on the long-term average (1981-2020). The value of 1 represents approximately one standard deviation of the surplus in the surface water balance, while the value of -1 is about one standard deviation of the deficit. Drought is usually defined as period when SPEI values fall below -1. Input precipitation data is downscaled from ERA5 reanalysis using quantile mapping. Contains modified Copernicus Climate Change Service information [1978-current year]; Contains modified Copernicus Atmosphere Monitoring Service information [1978-current year].
Land Surface Temperature - 231m 8 day mean

The Land Surface Temperature (LST) is based on MODIS satellite data. The LST is based on 8 day MOD11A2 (v006) LST products. The spatial resolution is 231 m after regridding from the original 1000 m resolution. The LST is masked to the highest quality standards using the provided quality layers. Missing pixel values in the time series are linearly interpolated. Non-vegetatated areas are masked using the MODIS land cover product layer MCD12Q1 FAO-Land Cover Classification System 1 (LCCS1). The final product is regridded to the LAEA Projection (EPSG:3035). The Land Surface Temperature is expressed in degree Celsius.
Copernicus Senwise RoseL-like imagery - Mazia Matsch catchment, South Tyrol, IT, 2025

The input RoseL-like imagery dataset is a copy of SAOCOM-1A SAR Stripmap dual pol (VH-VV) data collection downloaded from saocom.asi.it and covering the Glorenza-Merano region, including the Mazia-Matsch catchment, in South-Tyrol, Italy. Coordinates are [10.30, 46.92], [11.29, 46.34]. Data are in the Single Look Complex (SLC - Level-1A) format suitable for InSAR/PolSAR processing. Data are acquired in ascending (ASC) orbit and are given here in the SAR acquisition geometry (slant range, azimuth coordinates). Both extent and numbers of rows and columns vary a bit from one image to the other: values given here correspond to the 1st image of the collection. One geoprojected (.tif) image out of the collection is provided for information only, for allowing to locate the relevant area.
Copernicus Senwise RoseL-like imagery - Mazia Matsch catchment, South Tyrol, IT, 2024

The input RoseL-like imagery dataset is a copy of SAOCOM-1A SAR Stripmap dual pol (VH-VV) data collection downloaded from saocom.asi.it and covering the Glorenza-Merano region, including the Mazia-Matsch catchment, in South-Tyrol, Italy. Coordinates are [10.33, 46.91], [11.33, 46.28]. Data are in the Single Look Complex (SLC - Level-1A) format suitable for InSAR/PolSAR processing. Data are acquired in ascending (ASC) orbit and are given here in the SAR acquisition geometry (slant range, azimuth coordinates). Both extent and numbers of rows and columns vary a bit from one image to the other: values given here correspond to the 1st image of the collection. One geoprojected (.tif) image out of the collection is provided for information only, for allowing to locate the relevant area.
Copernicus Senwise RoseL-like imagery - Mazia Matsch catchment, South Tyrol, IT, 2023

The input RoseL-like imagery dataset is a copy of SAOCOM-1A SAR Stripmap dual pol (VH-VV) data collection downloaded from saocom.asi.it and covering the Glorenza-Merano region, including the Mazia-Matsch catchment, in South-Tyrol, Italy. Coordinates are [10.29, 46.96], [11.27, 46.38]. Data are in the Single Look Complex (SLC - Level-1A) format suitable for InSAR/PolSAR processing. Data are acquired in ascending (ASC) orbit and are given here in the SAR acquisition geometry (slant range, azimuth coordinates). Both extent and numbers of rows and columns vary a bit from one image to the other: values given here correspond to the 1st image of the collection. One geoprojected (.tif) image out of the collection is provided for information only, for allowing to locate the relevant area.
Copernicus Senwise RoseL-like imagery, Aix-en-Provence_Pennes-Mirabeau, FR 3, 2025

The input RoseL-like imagery dataset is a copy of SAOCOM-1B SAR Stripmap dual pol (VH-VV) data collection downloaded from saocom.asi.it. Data are in the Single Look Complex (SLC - Level-1A) format suitable for InSAR/PolSAR processing. Data cover the Aix-en-Provence region, in South of France, including the Pennes-Mirabeau area, where wildfires happened in Summer 2025. Coordinates are [5.23, 43.71], [5.85, 42.93]. Data are acquired in descending (DSC) orbit and are given here in the SAR acquisition geometry (slant range, azimuth coordinates). Both extent and numbers of rows and columns vary a bit from one image to the other: values given here correspond to the 1st image of the collection. One geoprojected (.tif) image out of the collection is provided for information only, for allowing to locate the relevant area.
Daily evaporation product Po basin

Evaporation (E) is the estimated flux of water evaporated from land surface, including vegetation and bare soil. The product is generated from Two-source Energy Balance (TSEB) model forced by ESA Copernicus Sentinel-2A/B MSI and Sentinel-3A/B SLSTR LST imagery together with ECMWF ERA5 reanalysis data. Evaporation maps are available at 100-m spatial resolution for the period 2017-2021 over Po basin in France. The spatial extent corresponds to Sentinel-2 tiling grids overlapping with the study area. The E layer contains one single band with evaporation values per day [mm/day] corresponding to Sentinel-3 acquisition day. Invalid pixels, mainly due to cloud contamination and lack of the input data for TSEB, are filled with NaN values. Evaporation outputs are generated in Cloud Optimized GeoTiff (COG) format with metadata included in the file attributes. Datasets are available for each month (Jan-Dec) of the year separately in the form of stacked daily E observations.
Daily evaporation product Medjerda basin

Evaporation (E) is the estimated flux of water evaporated from land surface, including vegetation and bare soil. The product is generated from Two-source Energy Balance (TSEB) model forced by ESA Copernicus Sentinel-2A/B MSI and Sentinel-3A/B SLSTR LST imagery together with ECMWF ERA5 reanalysis data. Evaporation maps are available at 100-m spatial resolution for the period 2017-2021 over Medjerda basin in France. The spatial extent corresponds to Sentinel-2 tiling grids overlapping with the study area. The E layer contains one single band with evaporation values per day [mm/day] corresponding to Sentinel-3 acquisition day. Invalid pixels, mainly due to cloud contamination and lack of the input data for TSEB, are filled with NaN values. Evaporation outputs are generated in Cloud Optimized GeoTiff (COG) format with metadata included in the file attributes. Datasets are available for each month (Jan-Dec) of the year separately in the form of stacked daily E observations.
Daily evaporation product Herault basin

Evaporation (E) is the estimated flux of water evaporated from land surface, including vegetation and bare soil. The product is generated from Two-source Energy Balance (TSEB) model forced by ESA Copernicus Sentinel-2A/B MSI and Sentinel-3A/B SLSTR LST imagery together with ECMWF ERA5 reanalysis data. Evaporation maps are available at 100-m spatial resolution for the period 2017-2021 over Herault basin in France. The spatial extent corresponds to Sentinel-2 tiling grids overlapping with the study area. The E layer contains one single band with evaporation values per day [mm/day] corresponding to Sentinel-3 acquisition day. Invalid pixels, mainly due to cloud contamination and lack of the input data for TSEB, are filled with NaN values. Evaporation outputs are generated in Cloud Optimized GeoTiff (COG) format with metadata included in the file attributes. Datasets are available for each month (Jan-Dec) of the year separately in the form of stacked daily E observations.
Daily evaporation product Ebro basin

Evaporation (E) is the estimated flux of water evaporated from land surface, including vegetation and bare soil. The product is generated from Two-source Energy Balance (TSEB) model forced by ESA Copernicus Sentinel-2A/B MSI and Sentinel-3A/B SLSTR LST imagery together with ECMWF ERA5 reanalysis data. Evaporation maps are available at 100-m spatial resolution for the period 2017-2021 over Ebro basin in France. The spatial extent corresponds to Sentinel-2 tiling grids overlapping with the study area. The E layer contains one single band with evaporation values per day [mm/day] corresponding to Sentinel-3 acquisition day. Invalid pixels, mainly due to cloud contamination and lack of the input data for TSEB, are filled with NaN values. Evaporation outputs are generated in Cloud Optimized GeoTiff (COG) format with metadata included in the file attributes. Datasets are available for each month (Jan-Dec) of the year separately in the form of stacked daily E observations.
Daily Height of Snow for the European Alps

S3M-Alps is a 500-m reanalysis of Snow Water Equivalent and Height of Snow for the European Alps. The product is driven by ERA5-Land meteorological reanalysis downscaled to 500 m using the MicroMet statistical–dynamical method (Liston and Elder, 2006). Downscaled meteorological fields are used to force the physically-based S3M snow model (Avanzi et al., 2022).
Daily Snow Water Equivalent for the European Alps

S3M-Alps is a 500-m reanalysis of Snow Water Equivalent for the European Alps. The product is driven by ERA5-Land meteorological reanalysis downscaled to 500 m using the MicroMet statistical–dynamical method (Liston and Elder, 2006). Downscaled meteorological fields are used to force the physically-based S3M snow model (Avanzi et al., 2022).
MODIS Leaf Area Index

The MCD15A3H Version 6.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Level 4 Leaf Area Index (LAI) product is a 4-day composite data set with 500 meter pixel size. The algorithm chooses the best pixel available from all the acquisitions of both MODIS sensors located on NASA’s Terra and Aqua satellites from within the 4-day period. LAI is defined as the one-sided green leaf area per unit ground area in broadleaf canopies and as one-half the total needle surface area per unit ground area in coniferous canopies.
MOD10A1 daily snow cover fraction for the Senales valley

This data set provides a daily snow cover fraction derived from the "MODIS/Terra Snow Cover 5-Min L2 Swath 500m" data set (DOI:10.5067/MODIS/MOD10_L2.061). The dataset is reprojected and regridded to a specific area of interest (Senales catchment). The original MODIS snow-cover products provide Normalized Difference Snow Index (NDSI) values from 0 – 100.  NDSI is then converted to snow cover fraction (SCF) from 0 – 100 (Salomonson and Appel, 2004; Riggs et al., 2019). Clouds are marked as 205.
LiDAR-derived Forest Mapping in Mazia valley

This dataset contains forest structural and species information derived from RGB-colored LiDAR point clouds collected by Eurac Research. Using a standardized R workflow (lidR, ForestTools), the LiDAR data were processed through ground classification, height normalization, canopy height model (CHM) generation, individual tree detection, crown segmentation, point-cloud tree assignment, and RGB-based unsupervised species clustering. The result is a set of spatial layers representing tree locations, tree crowns, canopy structure, and species group labels. These data products support forest monitoring, digital twin development, ecological analysis, and modelling of forest dynamics.
High resolution climatological large ensemble for the Alpine Region

The A-DROP LE is a single model initial condition large ensemble of the Alpine Region. It is based on the  Canadian Earth System Model 2 Large Ensemble (CanESM2-LE), that is dynamically downscaled with the Canadian Regional Climate Model (CRCM5) to 12 km spatial resolution (CRCM5-LE) over the European domain (Leduc et al., 2019). It consists of 5 climate variables (air temperature, dew point temperature, precipitation, incoming shortwave radiation and wind speed), that are bias-corrected via MBCn (Cannon, 2018) and statistically downscaled to a spatial resolution of 500 m using the method of Marke, 2008. The temporal resolution is sub-daily (every three hours).
Sciliar_Catinaccio

This collection is based on Sentinel-2 level 2A dataset acquired from both Sentinel-2 A and B satellites.
It covers a temporal range of 01-02-2021 to 30-09-2023, for every site all Sentinel scenes covering the area are included.
The collection includes all bands at a resolution of 10 meters. The bands are listed below.
B02
B03
B04
B05
B06
B07
B08
B8A
B09
B11
B12
SCL
The Level-2A data includes a Scene Classification, the algorithm allows the detection of clouds, snow and cloud shadows and generation of a classification map.
Cloud screening is applied to the data in order to retrieve accurate atmospheric and surface parameters during the atmospheric correction step.
The L2A SCL map can also be a valuable input for further processing steps or data analysis.
The collection covers all sites of the Hyperecos project. The following sites are included with the spatial extent mentioned.
Cireco {'west': 12.870775000000037, 'east': 13.103782000000024, 'south': 41.22186599400004, 'north': 41.41504699400008}
Orbetello {'west': 11.181888751927033,'east': 11.455397318265538, 'south': 42.372996996314896, 'north': 42.50311599528868}
Sciliar - Catinaccio {'west': 11.506713000000047, 'east': 11.667129000000045, 'south': 46.440615996000076, 'north': 46.54040999600005}
Castel Porziano {'west': 12.345466114000033, 'east': 12.451677663000055, 'south': 41.65575504100008, 'north': 41.78393419900004}
Monte Bondone {'west': 11.027602448000039, 'east': 11.044658587000072, 'south': 45.98801759300005, 'north': 46.01382867600006}
Bosco Fontana {'west': 10.73031770800003, 'east': 10.757708439000055, 'south': 45.192834764000054, 'north': 45.20899297600005}
Hunsrück-Hochwald {"west": 6.98720747225448, "east": 7.28904390300005, "north": 49.7943764377934, "south": 49.60530142600001}
MonteBondone

This collection is based on Sentinel-2 level 2A dataset acquired from both Sentinel-2 A and B satellites.
It covers a temporal range of 01-02-2021 to 30-09-2023, for every site all Sentinel scenes covering the area are included.
The collection includes all bands at a resolution of 10 meters. The bands are listed below.
B02
B03
B04
B05
B06
B07
B08
B8A
B09
B11
B12
SCL
The Level-2A data includes a Scene Classification, the algorithm allows the detection of clouds, snow and cloud shadows and generation of a classification map.
Cloud screening is applied to the data in order to retrieve accurate atmospheric and surface parameters during the atmospheric correction step.
The L2A SCL map can also be a valuable input for further processing steps or data analysis.
The collection covers all sites of the Hyperecos project. The following sites are included with the spatial extent mentioned.
Cireco {'west': 12.870775000000037, 'east': 13.103782000000024, 'south': 41.22186599400004, 'north': 41.41504699400008}
Orbetello {'west': 11.181888751927033,'east': 11.455397318265538, 'south': 42.372996996314896, 'north': 42.50311599528868}
Sciliar - Catinaccio {'west': 11.506713000000047, 'east': 11.667129000000045, 'south': 46.440615996000076, 'north': 46.54040999600005}
Castel Porziano {'west': 12.345466114000033, 'east': 12.451677663000055, 'south': 41.65575504100008, 'north': 41.78393419900004}
Monte Bondone {'west': 11.027602448000039, 'east': 11.044658587000072, 'south': 45.98801759300005, 'north': 46.01382867600006}
Bosco Fontana {'west': 10.73031770800003, 'east': 10.757708439000055, 'south': 45.192834764000054, 'north': 45.20899297600005}
Hunsrück-Hochwald {"west": 6.98720747225448, "east": 7.28904390300005, "north": 49.7943764377934, "south": 49.60530142600001}