Sentinel-2 imagery, S6, south-west Greenland, July 2017: Broadband albedo and surface type classification

This dataset consists 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, as applied to Sentinel-2 overpasses...

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Bibliographic Details
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"
UAS
albedo
ice
remote sensing
Greenland
Ice Sheet
Online Access:https://dx.doi.org/10.5285/8e0a573d-61a4-4a6f-9fca-fc34cbd5fb45
https://data.bas.ac.uk/full-record.php?id=GB/NERC/BAS/PDC/01292
Description
Summary:This dataset consists 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, as applied to Sentinel-2 overpasses of S6, K-transect, south-west Greenland on 20 and 21 July 2017. Funding was provided by the NERC standard grant NE/M021025/1. : Sentinel-2 imagery (European Space Agency) downloaded from Sinergise, Slovenia and converted from L1C to L2A reflectance using ESA Sen2Cor at 20 m resolution. Reflectance data ingested into a Random Forests classifier which was first trained on field data acquired in "Multi-spectral unmanned aerial system imagery, S6, south-west Greenland, July 2017: Levels 2 (ground reflectance) and 3 (broadband albedo and surface type classification)" (DOI: 10.5285/77ca631f-a3a4-4f26-bc90-57bb17baa6fc), in order to generate classification maps of ice sheet surface type across the study area. A narrowband-to-broadband albedo conversion was also applied following Liang (2001, Remote Sensing of Environment). : Instrumentation: MicaSense RedEdge multispectral camera integrated onto Steadidrone Mavrik-M quadcopter. ASD FieldSpec Pro 3. : Good. Sentinel-2 acquisitions used were clear-sky over study area of interest. See Tedstone et al. (2020, TC) for details of classifier algorithm accuracy.

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