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
The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.The v05.3 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2020-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.The data set should be cited using all three of the following references:1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-20192. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.0013. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 05.3
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 processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project
Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001
Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-2019
EARTH SCIENCE>SPECTRAL/ENGINEERING>RADAR
EARTH SCIENCE>AGRICULTURE>SOILS>SOIL MOISTURE/WATER CONTENT
METOP-A
METOP-B
ERS WIND SCATTEROMETER
ASCAT
Metop-A
Metop-B
AMI-SCAT
AMI/Scatterometer
Public data: access to these data is available to both registered and non-registered users.
ESA
Soil Moisture
CCI
Active
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
Rutherford Appleton Laboratory, Harwell
United Kingdom
CEDA
This dataset contains Level 3 nadir profile ozone data from the ESA Ozone Climate Change Initiative (CCI) project. The Level 3 data are monthly averages on a regular 3D grid derived from level 2 ozone profiles. In this version 2 of the dataset, data are available for 1997 and 2007 and 2008 only, and use data from the GOME instrument on ERS (1997) and the GOME-2 instrument on METOP-A (2007, 2008).
ESA Ozone Climate Change Initiative (Ozone CCI): Level 3 Nadir Ozone Profile Merged Data Product, version 2
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 processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC CHEMISTRY>OXYGEN COMPOUNDS>ATMOSPHERIC OZONE
METOP-A
METOP-B
ENVISAT
Aura
OMI
SCIAMACHY
GOME
Environmental Satellite
EOS
Metop
Royal Netherlands Meteorological Institute
ozone
Level 3
Envisat
MERGED
Metop-A
ozone nadir profile
month
ERS
SCanningÂ ImagingÂ Absorption spectroMeter forÂ Atmospheric CHartographY
Global Monitoring of Atmospheric Ozone
Ozone Monitoring Instrument
Global Monitoring of Atmospheric Ozone - 2
Metop-B
Public data: access to these data is available to both registered and non-registered users.
ESA
CCI
orthoimagery
Unavailable
ESA/CCI

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
This dataset is a monthly mean gridded total ozone data record (level 3) produced by the ESA Ozone Climate Change Initiative project (Ozone CCI). The dataset is a prototype of a merged harmonised ozone data record combining ozone data from the GOME instrument on ERS-2, the SCIAMACHY instrument on ENVISAT and the GOME-2 instrument on METOP-A, and covers the period between April 1996 to June 2011.
ESA Ozone Climate Change Initiative (Ozone CCI): Level 3 Total Ozone Merged Data Product, version 01
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 processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC CHEMISTRY>OXYGEN COMPOUNDS>ATMOSPHERIC OZONE
METOP-A
METOP-B
ENVISAT
SCIAMACHY
GOME
Environmental Satellite
Metop
Deutsches Zentrum fuer Luft- und Raumfahrt
Level 3S
ozone
Level 3
Envisat
MERGED
Metop-A
day
ozone total column
ERS
SCanningÂ ImagingÂ Absorption spectroMeter forÂ Atmospheric CHartographY
Global Monitoring of Atmospheric Ozone
Global Monitoring of Atmospheric Ozone - 2
Metop-B
Public data: access to these data is available to both registered and non-registered users.
ESA
CCI
orthoimagery
Unavailable
ESA/CCI

The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.The v05.2 COMBINED product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.The data set should be cited using all three of the following references:1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-20192. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.0013. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 05.2
Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project. This dataset forms part of the ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 05.2 data collection. doi: 10.5285/b11f3fa3303e46e6b0d44b058947a3f5. http://dx.doi.org/10.5285/b11f3fa3303e46e6b0d44b058947a3f5 .
Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001
Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070
Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717â739, https://doi.org/10.5194/essd-11-717-2019
EARTH SCIENCE>CLIMATE INDICATORS>LAND SURFACE/AGRICULTURE INDICATORS>SOIL MOISTURE
EARTH SCIENCE>SPECTRAL/ENGINEERING>MICROWAVE
EARTH SCIENCE>SPECTRAL/ENGINEERING>RADAR
EARTH SCIENCE>AGRICULTURE>SOILS>SOIL MOISTURE/WATER CONTENT
Aqua
CORIOLIS
DMSP 5D-2/F8
DMSP 5D-2/F11
DMSP 5D-2/F13
SMOS
TRMM
ERS WIND SCATTEROMETER
MIRAS
AMSR-E
ASCAT
SMMR
SSM/I
TMI
WINDSAT
soil moisture
Coriolis
AMI-SCAT
SMAP
AMSRE
WindSat
AQUA
AMI/Scatterometer
Soil Moisture
Combined

See the referenced specification
DE/DLR
Climatology Meteorology Atmosphere
The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational SO2 total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. GDP 4.x performs a DOAS fit for SO2 slant column followed by an AMF / VCD computation using a single wavelength. Corrections are applied to the slant column for equatorial offset, interference of SO2 and SO2 absorption, and SZA dependence. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/
METOP GOME-2 - Sulfur Dioxide (SO2) - Global
Nutzungsbedingungen: Lizenz, / Terms of use: License,
Please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages for more details on sulfur dioxide retrieval: https://atmos.eoc.dlr.de/app/docs/
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC CHEMISTRY>SULFUR COMPOUNDS>SULFUR DIOXIDE
METOP-C
Metop-C
Nutzungsbedingungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Terms of use: DLR not liable for damage resulting from use.
MetOp-A
MetOp-B
MetOp-C
Sulfur Dioxide
AC-SAF
GOME.TC.AGG
urn:eop:DLR:EOWEB:GOME.TC.AGG
FEDEO
Atmospheric conditions

See the referenced specification
DE/DLR
Climatology Meteorology Atmosphere
The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B, and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational ozone total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV / VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The new improved DOAS-style (Differential Optical Absorption Spectroscopy) algorithm called GDOAS, was selected as the basis for GDP version 4.0 in the framework of an ESA ITT. GDP 4.x performs a DOAS fit for ozone slant column and effective temperature followed by an iterative AMF / VCD computation using a single wavelength. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/
METOP GOME-2 - Ozone (O3) - Global
Nutzungsbedingungen: Lizenz, / Terms of use: License,
Please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages for more details on ozone total column retrieval: https://atmos.eoc.dlr.de/app/docs/
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC CHEMISTRY>OXYGEN COMPOUNDS>ATMOSPHERIC OZONE
METOP-C
Metop-C
Nutzungsbedingungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Terms of use: DLR not liable for damage resulting from use.
MetOp-A
MetOp-B
MetOp-C
Ozone
AC-SAF
GOME.TC.AGG
urn:eop:DLR:EOWEB:GOME.TC.AGG
FEDEO
Atmospheric conditions

See the referenced specification
DE/DLR
Environment
Every day, three successive NOAA-AVHRR scenes are used to derive a synthesis product in stereographic projection known as the "Normalized Difference Vegetation Index" for Europe and North Africa. It is calculated by dividing the difference in technical albedos between measurements in the near infrared and visible red part of the spectrum by the sum of both measurements. This value provides important information about the "greenness" and density of vegetation. Weekly and monthly thematic synthesis products are also derived from this daily operational product, at each step becoming successively free of clouds. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/
AVHRR - Vegetation Index (NDVI) - Europe
After reception of the AVHRR data a pre-processing routine delivers calibrated and auto-navigated data. These level 1 data are used for generating RGB - quicklooks overlayed with coastline and a so called media product which is a subset showing wide parts of Central Europe (“Central Europe”). The level 1 data are also used for generating value-added products such as the “Normalised Difference Vegetation Index” of Europe, the sea surface temperature of European seas and the land surface temperature of Europe representing a day-time or nighttime land surface temperature. For all value-added products different routines as e.g. cloud masking, georeferencing, including land-sea mask and compositing are necessary (level 2 data). The level 2 data are used for deriving daily, weekly and monthly level 3 products which are accessible by the internet (http://eoweb.dlr.de)Further information is available at http://wdc.dlr.de/sensors/avhrr/
EARTH SCIENCE>LAND SURFACE>LAND USE/LAND COVER
EARTH SCIENCE>LAND SURFACE>LAND USE/LAND COVER>LAND USE/LAND COVER CLASSIFICATION>VEGETATION INDEX
AVHRR
Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use.
Land cover
Vegetation Index
NDVI
Europe
urn:eop:DLR:EOWEB:NOAA.AVHRR.NDVI
FEDEO

Climatology Meteorology Atmosphere
The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. The operational H2O total column products are generated using the algorithm GDP (GOME Data Processor) version 4.x integrated into the UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) processor for generating level 2 trace gas and cloud products. The total H2O column is retrieved from GOME solar backscattered measurements in the red wavelength region (614-683.2 nm), using the Differential Optical Absorption Spectroscopy (DOAS) method. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/
METOP GOME-2 - Water Vapour (H2O) - Global
Nutzungsbedingungen: Lizenz, / Terms of use: License,
Please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages for more details on water vapour retrieval: https://atmos.eoc.dlr.de/app/docs/
EARTH SCIENCE>ATMOSPHERE>ATMOSPHERIC WATER VAPOR
METOP-C
Metop-C
Nutzungsbedingungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Terms of use: DLR not liable for damage resulting from use.
MetOp-A
MetOp-B
MetOp-C
Water Vapour
AC-SAF
GOME.TC.AGG
urn:eop:DLR:EOWEB:GOME.TC.AGG
Atmospheric conditions

The Global Ozone Monitoring Experiment-2 (GOME-2) instrument continues the long-term monitoring of atmospheric trace gas constituents started with GOME / ERS-2 and SCIAMACHY / Envisat. Currently, there are three GOME-2 instruments operating on board EUMETSAT's Meteorological Operational satellites MetOp-A, -B and -C, launched in October 2006, September 2012, and November 2018, respectively. GOME-2 can measure a range of atmospheric trace constituents, with the emphasis on global ozone distributions. Furthermore, cloud properties and intensities of ultraviolet radiation are retrieved. These data are crucial for monitoring the atmospheric composition and the detection of pollutants. DLR generates operational GOME-2 / MetOp level 2 products in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Chemistry Monitoring (AC-SAF). GOME-2 near-real-time products are available already two hours after sensing. OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks) are used for retrieving the following geophysical cloud properties from GOME and GOME-2 data: cloud fraction (cloud cover), cloud-top pressure (cloud-top height), and cloud optical thickness (cloud-top albedo). OCRA is an optical sensor cloud detection algorithm that uses the PMD devices on GOME / GOME-2 to deliver cloud fractions for GOME / GOME-2 scenes. ROCINN takes the OCRA cloud fraction as input and uses a neural network training scheme to invert GOME / GOME-2 reflectivities in and around the O2-A band. VLIDORT [Spurr (2006)] templates of reflectances based on full polarization scattering of light are used to train the neural network. ROCINN retrieves cloud-top pressure and cloud-top albedo. The cloud-top pressure for GOME scenes is derived from the cloud-top height provided by ROCINN and an appropriate pressure profile. For more details please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages: https://atmos.eoc.dlr.de/app/docs/
METOP GOME-2 - Cloud Top Pressure (CTP) - Global
Please refer to relevant peer-review papers listed on the GOME and GOME-2 documentation pages for more details on cloud top pressure retrieval: https://atmos.eoc.dlr.de/app/docs/
EARTH SCIENCE>ATMOSPHERE>CLOUDS>CLOUD PROPERTIES>CLOUD TOP PRESSURE
CTP
Cloud Top Pressure

Environment
The "Land Surface Temperature derived from NOAA-AVHRR data (LST_AVHRR)" is a fixed grid map (in stereographic projection) with a spatial resolution of 1.1 km. The total size covering Europe is 4100 samples by 4300 lines. Within 24 hours of acquiring data from the satellite, day-time and night-time LSTs are calculated. In general, the products utilise data from all six of the passes that the satellite makes over Europe in each 24 hour period. For the daily day-time LST maps, the compositing criterion for the three day-time passes is maximum NDVI value and for daily night-time LST maps, the criterion is the maximum night-time LST value of the three night-time passes. Weekly and monthly day-time or night-time LST composite products are also produced by averaging daily day-time or daily night-time LST values, respectively. The range of LST values is scaled between –39.5°C and +87°C with a radiometric resolution of 0.5°C. A value of –40°C is used for water. Clouds are masked out as bad values. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/
AVHRR - Land Surface Temperature (LST) - Europe, Nighttime
The LST maps are calculated using AVHRR channel 4 and 5, only. All LST products consist of one LST channel. The major processing steps are:1. Automatic pre-navigation / Interactive supervision 2. Calibration of thermal channels of NOAA-11, NOAA-14, NOAA-16, NOAA-17 and NOAA-18 AVHRR 3. Cloud Screening and Clearing 3.1. Cloud detection scheme for NIGHT TIME LST from NOAA-14 AVHRR 3.2. Cloud detection scheme for NIGHT TIME LST from NOAA-16 AVHRR 4. Derivation of the LST 5. Remapping Further information is available at http://wdc.dlr.de/sensors/avhrr/ and Dech, S., Tungalagsaikhan, P., Preusser, C., & Meisner, R., 1998. Operational value-adding to AVHRR data over Europe: methods, results, and prospects. Aerospace Science and Technology, 5, 335-346.
EARTH SCIENCE>LAND SURFACE>LAND USE/LAND COVER
AVHRR
Nutzungseinschränkungen: Das DLR ist nicht haftbar für Schäden, die sich aus der Nutzung ergeben. / Use Limitations: DLR not liable for damage resulting from use.
Land cover
Land Surface Temperature (nighttime)
Europe