NERC Data Catalogue Service
Contemporary (2016 - 2020) land cover classification across West Antarctica and the McMurdo Dry Valleys
We present here the land cover classification across West Antarctica and the McMurdo Dry Valley produced from Landsat-8 Operational Land Imager (OLI) images of six proglacial regions of Antarctica at 30 m resolution, with an overall accuracy of 77.0 % for proglacial land classes. We conducted this classification using an unsupervised K-means clustering approach, which circumvented the need for training data and was highly effective at picking up key land classes, such as vegetation, water, and different sedimentary surfaces.
This work is supported by the Leeds-York-Hull Natural Environment Research Council (NERC) Doctoral Training Partnership (DTP) Panorama under grant NE/S007458/1. The Ministry of Education, Youth and Sports of the Czech Republic project VAN 1/2022 and the Czech Antarctic Foundation funded fieldwork that contributed to part of this work.
Simple
- Alternate title
- Polar Data Centre (PDC) record GB/NERC/BAS/PDC/01652
- Date (Publication)
- 2022-07-14
- Identifier
- http://www.antarctica.ac.uk/dms/metadata.php?id= / GB/NERC/BAS/PDC/01652
- Maintenance and update frequency
- unknown Unknown
- Keywords
-
- NDGO0001
- NERC OAI Harvesting
-
- NERC_DDC
- GCMD Parameter Valids
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- EARTH SCIENCE > Biosphere > Vegetation
- EARTH SCIENCE > Land Surface > Erosion/Sedimentation
- EARTH SCIENCE > Land Surface > Land Use/Land Cover
- EARTH SCIENCE > Land Surface > Land Use/Land Cover > Land Cover
- BAS Free-text keywords
-
- Antarctica
- Google Earth Engine
- Land cover
- Landsat
- Sediment
- Vegetation
- Use limitation
- This data is covered by a UK Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/)
- Access constraints
- otherRestrictions Other restrictions
- Other constraints
- This data is covered by a UK Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/)
- Metadata language
- EnglishEnglish
- Topic category
-
- Environment
- Geoscientific information
- Imagery base maps earth cover
))
- Begin date
- 2016-02-02
- End date
- 2020-02-09
- Reference system identifier
- OGP / urn:ogc:def:crs:EPSG::4326
- Distribution format
-
- OnLine resource
- https://doi.org/10.5281/zenodo.6720051
- Hierarchy level
- dataset Dataset
Domain consistency
- Measure identification
- INSPIRE / Conformity_001
Conformance result
- Date
- Explanation
- See the referenced specification
- Pass
- No
- Statement
-
Accuracy assessed using the methods of:
Olofsson, P., Foody, G. M., Stehman, S. V, and Woodcock, C. E.: Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation, Remote Sens. Environ., 129, 122-131, https://doi.org/10.1016/j.rse.2012.10.031, 2013.
Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V, Woodcock, C. E., and Wulder, M. A.: Good practices for estimating area and assessing accuracy of land change, Remote Sens. Environ., 148, 42-57, https://doi.org/10.1016/j.rse.2014.02.015, 2014.
We found our classification to have an overall accuracy of 95.9 % overall. When just the proglacial land classes are considered, we have an accuracy of 77.0 %.
- File identifier
- GB_NERC_BAS_PDC_01652 XML
- Metadata language
- EnglishEnglish
- Hierarchy level
- dataset Dataset
- Date stamp
- 2022-07-14
- Metadata standard name
- NERC profile of ISO19115:2003
- Metadata standard version
- 1.0
Overviews
Spatial extent
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