Multi-spectral unmanned aerial system imagery, UPE_U, north-west Greenland, July 2018: Levels 2 (ground reflectance) and 3 (broadband albedo and surface type classification) ...

• Main Authors: Tedstone, Andrew, Cook, Joseph
• Format: Dataset
• Language: English
• Published: UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation 2020
• Subjects: "EARTH SCIENCE","CRYOSPHERE","GLACIERS/ICE SHEETS","ICE SHEETS"; "EARTH SCIENCE","CRYOSPHERE","SNOW/ICE","ALBEDO"; "EARTH SCIENCE","LAND SURFACE","LAND USE/LAND COVER"; "EARTH SCIENCE","LAND SURFACE","SURFACE RADIATIVE PROPERTIES","ALBEDO"; "EARTH SCIENCE","LAND SURFACE","SURFACE RADIATIVE PROPERTIES","REFLECTANCE"; UAS; albedo; ice; remote sensing; Greenland
• Online Access: https://dx.doi.org/10.5285/2dd66461-94af-458f-a9d2-c24bb0bd0322; https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01294

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. ... : 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. ...