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)

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.

Date (Creation): 2020-01-08

Date (Revision): 2020-01-08

Date (Publication): 2020-01-08

Date (released): 2020-01-08

Edition: 1.0

Unique resource identifier: https://doi.org/10.5285/2dd66461-94af-458f-a9d2-c24bb0bd0322

Codespace: doi

Unique resource identifier: GB/NERC/BAS/PDC/01294

Codespace: https://data.bas.ac.uk/

Unique resource identifier: NE/M021025/1

Codespace: award

Other citation details: Please cite this item as: Tedstone, A., & Cook, J. (2020). 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) (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/2dd66461-94af-458f-a9d2-c24bb0bd0322

Credit: No credit.

Status: Completed

Point of contact

Organisation name	Individual name	Electronic mail address	Role
University of Bristol	Tedstone, Andrew		Author
University of Sheffield	Cook, Joseph		Author
NERC EDS UK Polar Data Centre		PDCServiceDesk@bas.ac.uk	Point of contact

Maintenance and update frequency: As needed

Maintenance note: Completed

Global Change Master Directory (GCMD) Science Keywords

Theme

UAS
albedo
ice
remote sensing

Place

UPE_U, north-west Greenland Ice Sheet Greenland

GEMET - INSPIRE themes, version 1.0

Access constraints: Other restrictions

Other constraints: no limitations to public access

Access constraints: Other restrictions

Other constraints: no limitations

Use constraints: License

Other constraints: Open Government Licence v3.0

Use constraints: Other restrictions

Other constraints: This data is governed by the NERC Data Policy: https://www.ukri.org/who-we-are/nerc/our-policies-and-standards/nerc-data-policy/

Use constraints: Other restrictions

Other constraints: This data is governed by the NERC data policy and supplied under Open Government Licence v.3

Use constraints: Other restrictions

Other constraints: No restrictions apply.

Unique resource identifier: url

Codespace: url

Association Type: Cross reference

Unique resource identifier: url

Codespace: url

Association Type: Larger work citation

Unique resource identifier: doi

Codespace: doi

Association Type: Cross reference

Unique resource identifier: url

Codespace: url

Association Type: Cross reference

Unique resource identifier: url

Codespace: url

Association Type: Cross reference

Unique resource identifier: url

Codespace: url

Association Type: Cross reference

Unique resource identifier: doi

Codespace: doi

Association Type: Cross reference

Spatial representation type: Text, table

Language: English

Character set: UTF8

Topic category

Environment
Imagery base maps earth cover

Begin date: 2018-07-24

End date: 2018-07-24

Supplemental Information: 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.

Title: European Petroleum Survey Group (EPSG) Geodetic Parameter Registry

Date (Publication): 2008-11-12

Cited responsible party

Organisation name	Individual name	Electronic mail address	Role
European Petroleum Survey Group		EPSGadministrator@iogp.org	Publisher

Unique resource identifier: urn:ogc:def:crs:EPSG::3031

Version: 6.18.3

Distributor

Distributor contact

Organisation name	Individual name	Electronic mail address	Role
NERC EDS UK Polar Data Centre		PDCServiceDesk@bas.ac.uk	Distributor

Distributor format

Name	Version
application/x-hdf
application/netcdf

Units of distribution: bytes

Transfer size: 2254857830

OnLine resource

Protocol	Linkage	Name
WWW:LINK-1.0-http--link	https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=2dd66461-94af-458f-a9d2-c24bb0bd0322	Get Data

Units of distribution: bytes

Transfer size: 2254857830

OnLine resource

Protocol	Linkage	Name
WWW:LINK-1.0-http--link	https://ramadda.data.bas.ac.uk/repository/entry/show?entryid=2dd66461-94af-458f-a9d2-c24bb0bd0322	Get Data

Hierarchy level: Dataset

Statement: 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.

Data quality:

Good.

Metadata

File identifier: 2dd66461-94af-458f-a9d2-c24bb0bd0322 XML

Metadata language: English

Character set: UTF8

Hierarchy level: Dataset

Hierarchy level name: dataset

Date stamp: 2020-01-08

Metadata standard name: ISO 19115 Geographic Information - Metadata

Metadata standard version: ISO 19115:2003(E)

Metadata author

Organisation name	Individual name	Electronic mail address	Role
NERC EDS UK Polar Data Centre		polardatacentre@bas.ac.uk	Point of contact

Overviews

Spatial extent

Provided by

Access to the catalogue

Read here the full details and access to the data.

Simple

Distributor

Metadata

Overviews

Spatial extent

Keywords

Provided by

Share on social sites