EARTH SCIENCE > Land Surface > Surface Radiative Properties > Reflectance
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This dataset consists of orthomosaics created from flights of an unmanned aerial system imaging platform at S6 on the south-west Greenland K-transect during July 2017. Level-2 orthomosaics consist of (1) ground reflectance at 5 spectral bands, and (2) digital elevation models (only for 2017-07-20 and 2017-07-21). Level-3 orthomosaics consist of (1) broadband albedo calculated using a narrowband-to-broadband approximation and (2) surface type classification into snow, clean ice, light algae, heavy algae, cryoconite and water, as determined by a supervised classification algorithm. Training data ingested by the classification algorithm are also provided. Funding was provided by the NERC standard grant NE/M021025/1.
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This dataset consists of the unprocessed radiance measurements downloaded directly from the unmanned aerial system imaging platform used to image the ice sheet surface at S6 on the south-west Greenland K-transect during July 2017, along with captures of reflectance panels and sensor calibration parameters which enable these imagery to be transformed to reflectance measurements. Funding was provided by the NERC standard grant NE/M021025/1.
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This dataset consists of the unprocessed radiance measurements downloaded directly from the unmanned aerial system imaging platform used to image the ice sheet surface near UPE_U in the north-west of the Greenland Ice Sheet, along with captures of reflectance panels and sensor calibration parameters which enable these imagery to be transformed to reflectance measurements. Funding was provided by the NERC standard grant NE/M021025/1.
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This dataset consists of orthomosaics created from flights of an unmanned aerial system imaging platform at UPE_U in north-west Greenland on 24 July 2018. The Level-2 orthomosaics consist of (1) ground reflectance at 5 spectral bands, and (2) a digital elevation model. Level-3 orthomosaics consist of (1) broadband albedo calculated using a narrowband-to-broadband approximation and (2) surface type classification into snow, clean ice, light algae, heavy algae, cryoconite and water, as determined by a supervised classification algorithm which was trained on measurements collected at S6, K-transect, south-west Greenland. Funding was provided by the NERC standard grant NE/M021025/1.