Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
RAL Space, STFC Rutherford Appleton Laboratory, Harwell Campus
United Kingdom
CEDA
This dataset contains the Lakes Essential Climate Variable, which is comprised of processed satellite observations at the global scale, over the period 1992-2022, for over 2000 inland water bodies. This dataset was produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. For more information about the Lakes_cci please visit the project website. This is version 2.1.0 of the dataset.The six thematic climate variables included in this dataset are:â¢ Lake Water Level (LWL), derived from satellite altimetry, is fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate change.â¢ Lake Water Extent (LWE), modelled from the relation between LWL and high-resolution spatial extent observed at set time-points, describes the areal extent of the water body. This allows the observation of drought in arid environments, expansion in high Asia, or impact of large-scale atmospheric oscillations on lakes in tropical regions for example. .â¢ Lake Surface Water temperature (LSWT), derived from optical and thermal satellite observations, is correlated with regional air temperatures and is informative about vertical mixing regimes, driving biogeochemical cycling and seasonality.â¢ Lake Ice Cover (LIC), determined from optical observations, describes the freeze-up in autumn and break-up of ice in spring, which are proxies for gradually changing climate patterns and seasonality.â¢ Lake Water-Leaving Reflectance (LWLR), derived from optical satellite observations, is a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).â¢ Lake Ice Thickness (LIT), containing LIT information over Great Slave lake from 2002-2022.Data generated in the Lakes_cci are derived from multiple satellite sensors including: TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel 2-3, Landsat 4, 5, 7 and 8, ERS-1, ERS-2, Terra/Aqua and Metop-A/B.Satellite sensors associated with the thematic climate variables are as follows:LWL: TOPEX/Poseidon, Jason-1, Jason-2, Jason-3, Sentinel-6A, Envisat RA/RA-2, SARAL AltiKa, GFO, Sentinel-3A SRAL, Sentinel-3B SRAL, ERS-1 RA, ERS-2; LWE: Landsat 4 TM, 5 TM, 7 ETM+, 8 OLI, Sentinel-1 C-band SAR, Sentinel-2 MSI, Sentinel-3A SRAL, Sentinel-3B SRAL, ERS-1 AMI, ERS-2 AMI;LSWT: Envisat AATSR, Terra/Aqua MODIS, Sentinel-3A ATTSR-2, Sentinel-3B, ERS-2 AVHRR, Metop-A/B; LIC: Terra/Aqua MODIS; LWLR: Envisat MERIS, Sentinel-3A OLCI A/B, Aqua MODIS;LIT: Jason1, Jason2, Jason3, POSEIDON-2, POSEIDON-3 and POSEIDON-3B.Detailed information about the generation and validation of this dataset is available from the Lakes_cci documentation available on the project website and in Carrea, L., CrÃ©taux, JF., Liu, X. et al. Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies. Sci Data 10, 30 (2023). https://doi.org/10.1038/s41597-022-01889-z
ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 2.1
Under the following licence appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
This dataset was generated in the framework of the Lakes CCI+ project, funded by ESA. Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).
EARTH SCIENCE>ATMOSPHERE
EARTH SCIENCE>SPECTRAL/ENGINEERING>RADAR
EARTH SCIENCE>SPECTRAL/ENGINEERING>VISIBLE WAVELENGTHS
EARTH SCIENCE>BIOSPHERE>ECOSYSTEMS>FRESHWATER ECOSYSTEMS>LAKE/POND>MONTANE LAKE
ETM+
C-SAR
Sentinel-2 MSI
Envisat
Topex/Poseidon
ERS
Metop
SARAL
TOPEX/POSEIDON
TERRA
Metop-A
Metop-B
ETM
MSI
Public data: access to these data is available to both registered and non-registered users.
ESA
CCI
Lakes
ECV
orthoimagery
Unavailable

Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
RAL Space, STFC Rutherford Appleton Laboratory, Harwell Campus
United Kingdom
CEDA
This dataset contains various global lake products (1992-2019) produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. This is version 1.1 of the dataset.Lakes are of significant interest to the scientific community, local to national governments, industries and the wider public. A range of scientific disciplines including hydrology, limnology, climatology, biogeochemistry and geodesy are interested in distribution and functioning of the millions of lakes (from small ponds to inland seas), from the local to the global scale. Remote sensing provides an opportunity to extend the spatio-temporal scale of lake observation. The five thematic climate variables included in this dataset are:â¢ Lake Water Level (LWL): a proxy fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate changes.â¢ Lake Water Extent (LWE): a proxy for change in glacial regions (lake expansion) and drought in many arid environments, water extent relates to local climate for the cooling effect that water bodies provide.â¢ Lake Surface Water temperature (LSWT): correlated with regional air temperatures and a proxy for mixing regimes, driving biogeochemical cycling and seasonality. â¢ Lake Ice Cover (LIC): freeze-up in autumn and advancing break-up in spring are proxies for gradually changing climate patterns and seasonality. â¢ Lake Water-Leaving Reflectance (LWLR): a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).Data generated in the Lakes_cci project are derived from data from multiple instruments and multiple satellites including; TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel, Landsat, ERS, Terra/Aqua, Suomi NPP, Metop and Orbview. For more information please see the product user guide in the documents.
ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 1.1
Under the following licence appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
This dataset was generate in the framework of the Lakes CCI+ project, funded by ESA. Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).
EARTH SCIENCE>AGRICULTURE>SOILS
EARTH SCIENCE>ATMOSPHERE
EARTH SCIENCE>SPECTRAL/ENGINEERING>INFRARED WAVELENGTHS
EARTH SCIENCE>BIOSPHERE>ECOSYSTEMS>FRESHWATER ECOSYSTEMS>LAKE/POND>MONTANE LAKE
EARTH SCIENCE>SPECTRAL/ENGINEERING>RADAR
Aqua
ENVISAT
METOP-A
METOP-B
Terra
TOPEX/POSEIDON
ETM+
C-SAR
AATSR
MERIS
MODIS
MSS
OLI
RA
SeaWiFS
SSALT
TM
OLCI
day
Collecte Localisation Satellites
Laboratoire d'Etudes en Geodesie et Oceanographie Spatiales
Plymouth Marine Laboratory
Envisat
GFO
Metop-A
Metop-B
SARAL
SNPP
Topex/Poseidon
Level 3
Level 3S
MERGED
AltiKa
VIIRS
lakes
multiple lake products
SRAL
University of Reading
H2O Geomatics
AQUA
TERRA
ETM
Public data: access to these data is available to both registered and non-registered users.
ESA
CCI
Lakes
ECV
orthoimagery
Unavailable

Italy
This data set is conformant with the INSPIRE Implementing Rules for the interoperability of spatial data sets and services
Largo Galileo Galilei 1
ESA/ESRIN
Imagery Base Maps Earth Cover
This dataset contains the cloud-free products from Landsat 7 Enhanced Thematic Mapper collection acquired over Europe, North Africa and middle East; for each scene only one product is selected, with the minimal cloud coverage. The Landsat 7 ETM+ scenes typically cover 185 x 170 km. A standard full scene is nominally centred on the intersection between a Path and Row (the actual image centre can vary by up to 100m). The data are system corrected.
Landsat 7 ETM+ European and Mediterranean Countries Cloud Free Collection
No info available.
European Space Agency, 2022, Landsat ETM+ Cloud-Free Collection, Version SLAP_03.08
EARTH SCIENCE>LAND SURFACE>SURFACE RADIATIVE PROPERTIES
EARTH SCIENCE>BIOSPHERE>VEGETATION
EARTH SCIENCE>LAND SURFACE>LAND USE/LAND COVER
ETM+
Orthoimagery
Surface Radiative Properties
Vegetation
Land Use and Land Cover
Sun-synchronous
High Resolution - HR (5 - 20) m
Medium Resolution - MR (20 - 500) m
Imaging Spectrometers/Radiometers
PUBLIC
ETM
conditions to access and use unknown
Utilisation of this data is subject to the Terms and Conditions for ESA's Third Party Missions scheme

DOI/USGS
Geoscientific Information
CLIMATE APPLICATIONS: Climate change, surface hydrologic modeling, biogeochemical cycling, water supply and availability
EARTH SCIENCE>BIOSPHERE>ECOSYSTEMS>FRESHWATER ECOSYSTEMS>LAKE/POND>MONTANE LAKE
Lakes
ECV

ESA/ESRIN
Geoscientific Information
Global Land Ice Measurements from Space (GLIMS) Glacier database (glims.org), Randolph Glacier Inventory (RGI) (glims.org/RGI). CLIMATE APPLICATIONS: Water resources assessment and hydrological impacts on regional scales. Calculation of the contribution of glaciers to sea level rise. Unique demonstrator of climate change impacts for a large public audience. Attribution of climate change to anthropogenic causes. Validation of climate models.
EARTH SCIENCE>CRYOSPHERE>GLACIERS/ICE SHEETS>GLACIER ELEVATION/ICE SHEET ELEVATION
Terra
TM
OLI
Sentinel-2 MSI
ASTER
TERRA
MSI
Glaciers and Ice Caps

DOI/USGS
OpenGeoHub Foundation
Brazil, cloud-free, and reconstructed historical Landsat spectral bands are provided at a spatial resolution of 30 meters and temporal resolution of yearly intervals (derived by percentile 50th aggregation of bimonthly images) spanning from 1997 onwards. The dataset was generated using the GLAD Landsat Analysis Ready Data version 2 as the primary input for temporal aggregation and the imputation of missing values. Detailed information on the data processing methodology in [Consoli et al., 2024](https://peerj.com/articles/18585/). This subset of the collection provides Brazil mosaics for all Landsat bands (RGB, NIR, SWIR-1, SWIR-2 & Thermal) as Cloud Optimized GeoTIFF (COG).
Landsat TSIRF yearly
OLI
TIRS
TM
Landsat
landsat
oli
tirs
etm
tm
cloud optimized geotiff
cog
earth observation
brazil

DOI/USGS
BR/INPE
Landsat Historical Data Archive of the Image Generation Laboratory (LGI) at National Institute for Space Reaserch (INPE). This dataset includes the folliwing Landsat Missions: Landsat-1/2/3 MSS, Landsat-4/5 TM, Landsat-7 ETM and Landsat-8 OLI.
Landsat INPE Data Archive
MSS
Landsat
lgi
landsat
oli
etm
mss
tm
digital number
zip
earth observation
brazil

Landsat Collection 2 - Level-2 - Data Cube - LCF 16 days
Earth Observation Data Cube generated from Landsat Level-2 product over Brazil extension. This dataset is provided in Cloud Optimized GeoTIFF (COG) file format. The dataset is processed with 30 meters of spatial resolution, reprojected and cropped to BDC_MD grid Version 2 (BDC_MD V2), considering a temporal compositing function of 16 days using the Least Cloud Cover First (LCF) best pixel approach.
EARTH SCIENCE>LAND SURFACE>SURFACE RADIATIVE PROPERTIES>REFLECTANCE
EARTH SCIENCE>LAND SURFACE>LAND USE/LAND COVER>LAND USE/LAND COVER CLASSIFICATION>VEGETATION INDEX
TIRS
Landsat
data cube
landsat
surface reflectance
vegetation index
cloud optimized geotiff
cog
earth observation
brazil
tm
etm
oli
tirs

COMMISSION REGULATION (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
non testé
Reflectance Landsat images (Level 2A) processed by the Theia Land Data Center (http://www.theia-land.fr) for the CNES French Space Agency (http://www.cnes.fr). The processing center developed by CNES uses the MACCS prototype L2A chain developed and designed by CESBIO. LANDSAT 8 L1T Input data come from USGS (http://earthexplorer.usgs.gov) that we would like to thank for releasing freely the LANDSAT 8 datasets.
Landsat Level2A images (Theia)
LANDSAT 5 7 8 - ETM, TM, OLI, TIRS
Geology
Land cover
EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC RADIATION > REFLECTANCE
FedEO
THEIA
muscate
reflectance
CNES
18 avenue Edouard Belin
France
FR/CNES

Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
Rutherford Appleton Laboratory, Harwell
United Kingdom
CEDA
Dara are ESRI vector shape-file format and include metadata information on the sensor and processing steps in the corresponding attribute table
The data set provides calving front locations of 28 major outlet glaciers of the Greenland Ice Sheet, produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. The Calving Front Location (CFL) of outlet glaciers from ice sheets is a basic parameter for ice dynamic modelling, for computing the mass fluxes at the calving gate, and for mapping glacier area change. The calving front location has been derived by manual delineation using SAR (Synthetic Aperture Radar) data from the ERS-1/2, Envisat and Sentinel-1 satellites and satellite imagery from LANDSAT 5,7,8. The digitized calving fronts are stored in ESRI vector shape-file format and include metadata information on the sensor and processing steps in the corresponding attribute table.The product was generated by ENVEO (Environmental Earth Observation Information Technology GmbH)
ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Calving Front Locations, v3.0
Under the following licence appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were produced by ENVEO (Environmental Earth Observation Information Technology GmbH) as part of the ESA CCI Greenland Ice Sheet project and were supplied to CEDA in the context of the ESA CCI Open Data Portal Project.
EARTH SCIENCE>CRYOSPHERE>GLACIERS/ICE SHEETS>ICE SHEETS
EARTH SCIENCE>AGRICULTURE>SOILS
C-SAR
AMI
TIRS
ice sheets
AMI-SAR
SAR-C (Sentinel-1)
AMI/SAR
Public data: access to these data is available to both registered and non-registered users.
Greenland
Ice sheet
CCI
ESA
orthoimagery
ESA/CCI