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A Method of Retrieving 10-m Spectral Surface Albedo Products from Sentinel-2 and MODIS data

Song, R; Muller, JP; Francis, A; (2021) A Method of Retrieving 10-m Spectral Surface Albedo Products from Sentinel-2 and MODIS data. In: International Geoscience and Remote Sensing Symposium (IGARSS). (pp. pp. 2381-2384). IEEE: Brussels, Belgium. Green open access

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Abstract

This study proposed a new method of retrieving 10-m spectral surface albedo products. Three crucial components are incorporated into this high-resolution surface albedo generation system. Firstly, a deep learning system, CloudFCN based on the U-net paradigm has been developed. This produces the best available cloud detection of any algorithm published to date. Secondly, an advanced atmospheric correction model, the Sensor Invariant Atmospheric Correction (SIAC) is employed. The SIAC method considers the surface BRDF effects as these are usually ignored, because the atmosphere correction is a large signal and the largest uncertainty in converting top-of-atmosphere reflectance to top-of-canopy surface reflectance. Thirdly, an endmember-based new technology will be used to retrieve high-resolution albedo from high-resolution reflectance by combining downscaled MODIS BRDF. These methods are further described alongside results shown of the different stages and the final high resolution albedo.

Type: Proceedings paper
Title: A Method of Retrieving 10-m Spectral Surface Albedo Products from Sentinel-2 and MODIS data
Event: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS
Dates: 11 Jul 2021 - 16 Jul 2021
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/IGARSS47720.2021.9554356
Publisher version: https://doi.org/10.1109/IGARSS47720.2021.9554356
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Reflectivity, Cloud computing, Uncertainty, Atmospheric modeling, Poles and towers, Land surface, Spatial resolution
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Space and Climate Physics
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10149985
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