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Directional Effects on Land Surface Temperature Estimation From Meteosat Second Generation for Savanna Landscapes

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4 Author(s)
Mads Olander Rasmussen ; Department of Geography and Geology, University of Copenhagen, Copenhagen, Denmark ; Frank-M. Gottsche ; Folke-Sören Olesen ; Inge Sandholt

Structured canopies can show pronounced directional effects which influence land surface temperature (LST) estimates from thermal infrared satellite data. The effects depend on illumination and viewing geometries, because changes in these two geometries effectively cause the sensor to “see” different fractions of the canopy and the “background” surface (bare soil or low vegetation). Furthermore, parts of these two components will be in shadow, depending on the specific geometry of the canopy and its structure. This paper investigates these directional effects for a specific savanna site in West Africa and extends the findings to areas with denser tree crown cover. This is achieved by modeling the combined effects of the structured surface with a geometric optics model. The model assumes that the surface consists of four components: shaded and sunlit tree canopies and shaded and sunlit backgrounds. The brightness temperatures of these four surface components are provided by in situ measurements at the validation site, and emissivities are taken from the Land Surface Analysis Satellite Applications Facility (LSA-SAF) project. The LST modeling is performed for the geometry of the geostationary Meteosat Second Generation and for nadir geometry. Analyses of the temperature differences between the LST estimates for the two geometries show that, in many cases, the directional effects exceed 1°C within a day and that the timing and the sign of the effects change with season. Directional errors due to structured canopies are currently not considered in error estimates of operationally available LST products, e.g., the LSA-SAF LST product or the Moderate Resolution Imaging Spectroradiometer (MODIS) LST/emissivity products.

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IEEE Transactions on Geoscience and Remote Sensing  (Volume:49 ,  Issue: 11 )