Articles | Volume 17, issue 20
https://doi.org/10.5194/amt-17-6025-2024
https://doi.org/10.5194/amt-17-6025-2024
Research article
 | 
17 Oct 2024
Research article |  | 17 Oct 2024

HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and TEmporal Resolution

Giulia Roccetti, Luca Bugliaro, Felix Gödde, Claudia Emde, Ulrich Hamann, Mihail Manev, Michael Fritz Sterzik, and Cedric Wehrum

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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Cited articles

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Short summary
The amount of sunlight reflected by the Earth’s surface (albedo) is vital for the Earth's radiative system. While satellite instruments offer detailed spatial and temporal albedo maps, they only cover seven wavelength bands. We generate albedo maps that fully span the visible and near-infrared range using a machine learning algorithm. These maps reveal how the reflectivity of different land surfaces varies throughout the year. Our dataset enhances the understanding of the Earth's energy balance.