77ca631f-a3a4-4f26-bc90-57bb17baa6fc eng utf8 dataset dataset NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom polardatacentre@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact 2020-01-08 ISO 19115 Geographic Information - Metadata ISO 19115:2003(E) European Petroleum Survey Group (EPSG) Geodetic Parameter Registry 2008-11-12 publication European Petroleum Survey Group EPSGadministrator@iogp.org https://www.epsg-registry.org/ EPSG Geodetic Parameter Dataset The EPSG Geodetic Parameter Dataset is a structured dataset of Coordinate Reference Systems and Coordinate Transformations, accessible through this online registry. information publisher urn:ogc:def:crs:EPSG::3031 6.18.3 Multi-spectral unmanned aerial system imagery, S6, south-west Greenland, July 2017: Levels 2 (ground reflectance) and 3 (broadband albedo and surface type classification) 2020-01-08 creation 2020-01-08 revision 2020-01-08 publication 2020-01-08 released 1.0 https://doi.org/10.5285/77ca631f-a3a4-4f26-bc90-57bb17baa6fc doi GB/NERC/BAS/PDC/01293 https://data.bas.ac.uk/ NE/M021025/1 award Please cite this item as: Tedstone, A., & Cook, J. (2020). Multi-spectral unmanned aerial system imagery, S6, south-west Greenland, July 2017: Levels 2 (ground reflectance) and 3 (broadband albedo and surface type classification) (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/77ca631f-a3a4-4f26-bc90-57bb17baa6fc 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. No credit. completed Tedstone, Andrew University of Bristol Researcher author Cook, Joseph University of Sheffield Researcher author NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information pointOfContact asNeeded completed EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Ice Sheets EARTH SCIENCE > Cryosphere > Snow/Ice > Albedo EARTH SCIENCE > Land Surface > Land Use/Land Cover > Land Cover EARTH SCIENCE > Land Surface > Surface Radiative Properties > Albedo EARTH SCIENCE > Land Surface > Surface Radiative Properties > Reflectance theme Global Change Master Directory (GCMD) Science Keywords 2026-01-27 publication 23 Global Change Data Center, Science and Exploration Directorate, Goddard Space Flight Center (GSFC) National Aeronautics and Space Administration (NASA) Greenbelt MD United States of America https://earthdata.nasa.gov/about/gcmd/global-change-master-directory-gcmd-keywords Global Change Master Directory (GCMD) Keywords The information provided on this page seeks to define how the GCMD Keywords are structured, used and accessed. It also provides information on how users can participate in the further development of the keywords. information publisher UAS albedo ice remote sensing theme S6, K-Transect, south-west Greenland Ice Sheet Greenland place Elevation Meteorological geographical features Land cover theme GEMET - INSPIRE themes, version 1.0 2021-01-06 revision otherRestrictions no limitations to public access otherRestrictions no limitations license Open Government Licence v3.0 otherRestrictions This data is governed by the NERC Data Policy: https://www.ukri.org/who-we-are/nerc/our-policies-and-standards/nerc-data-policy/ otherRestrictions This data is governed by the NERC data policy and supplied under Open Government Licence v.3 otherRestrictions No restrictions apply. url url largerWorkCitation doi doi crossReference doi doi crossReference url url crossReference url url crossReference url url crossReference url url crossReference textTable eng utf8 environment imageryBaseMapsEarthCover -49.35 -49.35 67.08 67.08 2017-07-15 2017-07-24 It is recommended that careful attention be paid to the contents of any data, and that the author be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to polardatacentre@bas.ac.uk. NERC EDS UK Polar Data Centre +44 (0)1223 221400 British Antarctic Survey, High Cross, Madingley Road Cambridge Cambridgeshire CB3 0ET United Kingdom PDCServiceDesk@bas.ac.uk https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/ information distributor text/plain text/csv application/x-hdf application/netcdf bytes 9771050598 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=77ca631f-a3a4-4f26-bc90-57bb17baa6fc WWW:LINK-1.0-http--link Get Data Download data download bytes 9771050598 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=77ca631f-a3a4-4f26-bc90-57bb17baa6fc WWW:LINK-1.0-http--link Get Data Download data download bytes 9771050598 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=77ca631f-a3a4-4f26-bc90-57bb17baa6fc WWW:LINK-1.0-http--link Get Data Download data download bytes 9771050598 https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=77ca631f-a3a4-4f26-bc90-57bb17baa6fc WWW:LINK-1.0-http--link Get Data Download data download dataset Methodology: 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. Briefly, we used 171 directional reflectance measurements. The measurements were labelled by visual examination as snow ('SN'), water ('WA'), clean ice ('CI'), light algae ('LA'), heavy algae ('HA') and dispersed cryoconite ('CC'). After ground spectra were acquired we took destructive ground samples (see Tedstone et al 2020 TC for more details). We split the field dataset randomly into training (70%) and test (30%) sets. These data were used to train a Random Forest classifier. We trained the algorithm to predict surface type, utilising all 5 bands of data. Narrowband-to-broadband approximations for albedo calculations were employed because empirical Bi-directional Reflectance Distribution Functions (BRDFs) are not available for the surface types that we mapped. We used the photogrammetric DEMs to derive (i) study area slope angle and (ii) local topographic variability. To calculate the slope angle we applied a gaussian filter with a window of 0.25 m to remove very-high-frequency topographic features, then we calculated the average slope across each study area. To examine local topographic variability ('roughness') we applied a gaussian filter with a window of 4.95 m, then subtracted it from the DEM to yield a detrended surface. Data collection: Instrumentation: MicaSense RedEdge multispectral camera integrated onto Steadidrone Mavrik-M quadcopter. ASD FieldSpec Pro 3. Data quality: Good. Flights only undertaken on clear-sky days unless otherwise specified. asNeeded completed