Multi-spectral unmanned aerial system imagery, S6, south-west Greenland, July 2017: Levels 2 (ground reflectance) and 3 (broadband albedo and surface type classification) ...
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 an...
Main Authors: | , |
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Format: | Dataset |
Language: | English |
Published: |
UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation
2020
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Online Access: | https://dx.doi.org/10.5285/77ca631f-a3a4-4f26-bc90-57bb17baa6fc https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01293 |
Summary: | 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. ... : Multispectral imagery were acquired using a MicaSense RedEdge camera mounted on a Steadidrone Mavik-M quadcopter flown at a height of 30 m above the ice surface with 60% overlap and 40% sidelap. Radiometric calbiration and geometric distortion correction applied in post-processing. Data converted from radiance to reflectance using calibrated reflectance panels. Images mosaiced using AgiSoft PhotoScan at 5 cm final ground resolution. The orthomosaics were used in three ways: (i) converted to albedo using a narrowband-to-broadband approximation (Knap et al 1999, Int. J. Remote Sens.), (ii) classified into surface types, and (iii) digital elevation models derived photogrametrically in Agisoft PhotoScan at 5 cm ground resolution. To classify images by surface type we used a supervised classification approach following Cook et al. (2020, The Cryosphere), trained on ground spectra collected at S6 with a FieldSpec Pro 3 (Analytical Spectral Devices, Boulder, USA) during the 2016 and 2017 field seasons at S6. ... |
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