Atmospheric and spectral corrections for estimating surface albedo from satellite data
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Land surface broadband albedo is one of the most important physical parameters for climate models, because it governs the exchange of radiation between the land surface and the atmosphere. It depends on the atmospheric conditions through downward fluxes. Satellite remote sensing techniques provide a more accurate pixel-level estimation of surface albedo than traditional field measurements. However, atmospheric effects and band pass limits of satellite sensors are two factors that limit accurate estimation of surface albedo from satellite data. This paper develops a method for making atmospheric and spectral corrections for estimating surface albedo from satellite data. We applied an approach that decouples surface reflectance spectra from radiative transfer simulations so that many different surface reflectance spectra and the atmospheric conditions can be effectively incorporated for calculating the total shortwave albedo, total-, direct-, and diffuse-visible, and near-infrared broadband albedos for several satellite data LANDSAT TM and ETM.
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