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/10.5285/77ca631f-a3a4-4f26-bc90-57bb17baa6fc

Codespace

doi

Unique resource identifier

GB/NERC/BAS/PDC/01293

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, 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

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

• 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

• UAS

• albedo

• ice

• remote sensing

Place

• S6, K-Transect, south-west Greenland Ice Sheet Greenland

GEMET - INSPIRE themes, version 1.0

• Elevation
• Meteorological geographical features
• Land cover

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

Larger work citation

Unique resource identifier

doi

Codespace

doi

Association Type

Cross reference

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

url

Codespace

url

Association Type

Cross reference

Spatial representation type

Text, table

Language

English

Character set

UTF8

Topic category

• Environment
• Imagery base maps earth cover

Begin date

2017-07-15

End date

2017-07-24

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

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.

ASD FieldSpec Pro 3.

Data quality:

Good. Flights only undertaken on clear-sky days unless otherwise specified.

Metadata

File identifier

77ca631f-a3a4-4f26-bc90-57bb17baa6fc 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