Abstract
Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the European Space Agency (ESA) Sentinel 3 (S3) satellite, accurate LST retrieval methodologies are being developed by exploiting the synergy between the Ocean and Land Colour Instrument (OLCI) and the Sea and Land Surface Temperature Radiometer (SLSTR). In this paper we explain the implementation in the Basic ENVISAT Toolbox for (A)ATSR and MERIS (BEAM) and the use of one LST algorithm developed in the framework of the Synergistic Use of The Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST) project. The LST algorithm is based on the split-window technique with an explicit dependence on the surface emissivity. Performance of the methodology is assessed by using MEdium Resolution Imaging Spectrometer/Advanced Along-Track Scanning Radiometer (MERIS/AATSR) pairs, instruments with similar characteristics than OLCI/ SLSTR, respectively. The LST retrievals were properly validated against in situ data measured along one year (2011) in three test sites, and inter-compared to the standard AATSR level-2 product with satisfactory results. The algorithm is implemented in BEAM using as a basis the MERIS/AATSR Synergy Toolbox. Specific details about the processor validation can be found in the validation report of the SEN4LST project.
Highlights
The Sentinel satellite constellation series is developed by the European Space Agency (ESA) in order to support European operational services and the policy needs of the Copernicus programme.The first three Sentinel missions contribute to the understanding of the Earth System by detecting, monitoring and assessing changes in ocean, cryosphere, and land components [1,2]
Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST)” [6,7], which had the main objective to fully utilize the synergy between Sea and Land Surface Temperature Radiometer (SLSTR) and Ocean and Land Colour Instrument (OLCI) instruments to improve atmospheric correction and land surface emissivity (LSE) characterization for a better estimation of the land surface temperature (LST)
The surface reflectances retrieved from the MERIS and AATSR sensors are necessary for a correct estimation of the LSE using the normalized difference vegetation index (NDVI)-thresholds method (THM) method introduced before [18]
Summary
The Sentinel satellite constellation series is developed by the European Space Agency (ESA) in order to support European operational services and the policy needs of the Copernicus programme. One of the main objectives of the S3 mission is to provide Europe with continuity of the ENVISAT type measurement capability to determine sea, ice and land surface temperature. In this context, ESA funded the project “Synergistic Use of The. Sentinel Missions For Estimating And Monitoring Land Surface Temperature (SEN4LST)” [6,7], which had the main objective to fully utilize the synergy between SLSTR and OLCI instruments to improve atmospheric correction (including cloud screening) and land surface emissivity (LSE) characterization for a better estimation of the land surface temperature (LST). Because there are still not available pairs of the OLCI/SLSTR, simulated data is used instead [9]
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