Monitoring Vegetation Biomass in Continental Antarctica: A Comparison of Hyper- and Multispectral Imagery
In the last few decades Antarctica has come under intense scrutiny as an area that could potentially provide insight into climate change as an early warning system for the rest of the world. This is due in part to the vegetation that inhabits the area which includes populations of lichen, algae and...
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ftdatacite:10.7488/era/920 2023-05-15T13:56:39+02:00 Monitoring Vegetation Biomass in Continental Antarctica: A Comparison of Hyper- and Multispectral Imagery White, Megan 2020 https://dx.doi.org/10.7488/era/920 https://era.ed.ac.uk/handle/1842/37639 unknown The University of Edinburgh Remote Sensing, Sentinel-2, Biological Soil Crusts, Antarctica, Supervised Classification, Random Forest, Spectral Unmixing CreativeWork article 2020 ftdatacite https://doi.org/10.7488/era/920 2021-11-05T12:55:41Z In the last few decades Antarctica has come under intense scrutiny as an area that could potentially provide insight into climate change as an early warning system for the rest of the world. This is due in part to the vegetation that inhabits the area which includes populations of lichen, algae and moss. Also known as biological soil crusts, lichen, algae and moss have all been proven to be indicators of climate change and pollution. The Antarctic environment has the advantage of being mostly untouched by the influence of humanity and other environmental factors. This allows for a pure environment for the study of how climate change affects the distribution of vegetation. The recent availability of the Sentinel-2 satellite constellation provides researchers with an opportunity to increase the scale of vegetation surveys beyond what manual surveys can conduct. In this study a random forest algorithm is applied to UAV hyperspectral imagery and spectral unmixing is applied to Sentinel-2 imagery. A spectral library extracted from the UAV imagery is used to conduct the spectral unmixing of 10m resolution satellite imagery. The outcome was a comparison of the effectiveness of the two different resolutions and the creation of a classification map for the diversity of Biological Soils Crusts in the Antarctic environment. Article in Journal/Newspaper Antarc* Antarctic Antarctica DataCite Metadata Store (German National Library of Science and Technology) Antarctic The Antarctic The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
Remote Sensing, Sentinel-2, Biological Soil Crusts, Antarctica, Supervised Classification, Random Forest, Spectral Unmixing |
spellingShingle |
Remote Sensing, Sentinel-2, Biological Soil Crusts, Antarctica, Supervised Classification, Random Forest, Spectral Unmixing White, Megan Monitoring Vegetation Biomass in Continental Antarctica: A Comparison of Hyper- and Multispectral Imagery |
topic_facet |
Remote Sensing, Sentinel-2, Biological Soil Crusts, Antarctica, Supervised Classification, Random Forest, Spectral Unmixing |
description |
In the last few decades Antarctica has come under intense scrutiny as an area that could potentially provide insight into climate change as an early warning system for the rest of the world. This is due in part to the vegetation that inhabits the area which includes populations of lichen, algae and moss. Also known as biological soil crusts, lichen, algae and moss have all been proven to be indicators of climate change and pollution. The Antarctic environment has the advantage of being mostly untouched by the influence of humanity and other environmental factors. This allows for a pure environment for the study of how climate change affects the distribution of vegetation. The recent availability of the Sentinel-2 satellite constellation provides researchers with an opportunity to increase the scale of vegetation surveys beyond what manual surveys can conduct. In this study a random forest algorithm is applied to UAV hyperspectral imagery and spectral unmixing is applied to Sentinel-2 imagery. A spectral library extracted from the UAV imagery is used to conduct the spectral unmixing of 10m resolution satellite imagery. The outcome was a comparison of the effectiveness of the two different resolutions and the creation of a classification map for the diversity of Biological Soils Crusts in the Antarctic environment. |
format |
Article in Journal/Newspaper |
author |
White, Megan |
author_facet |
White, Megan |
author_sort |
White, Megan |
title |
Monitoring Vegetation Biomass in Continental Antarctica: A Comparison of Hyper- and Multispectral Imagery |
title_short |
Monitoring Vegetation Biomass in Continental Antarctica: A Comparison of Hyper- and Multispectral Imagery |
title_full |
Monitoring Vegetation Biomass in Continental Antarctica: A Comparison of Hyper- and Multispectral Imagery |
title_fullStr |
Monitoring Vegetation Biomass in Continental Antarctica: A Comparison of Hyper- and Multispectral Imagery |
title_full_unstemmed |
Monitoring Vegetation Biomass in Continental Antarctica: A Comparison of Hyper- and Multispectral Imagery |
title_sort |
monitoring vegetation biomass in continental antarctica: a comparison of hyper- and multispectral imagery |
publisher |
The University of Edinburgh |
publishDate |
2020 |
url |
https://dx.doi.org/10.7488/era/920 https://era.ed.ac.uk/handle/1842/37639 |
long_lat |
ENVELOPE(73.317,73.317,-52.983,-52.983) |
geographic |
Antarctic The Antarctic The Sentinel |
geographic_facet |
Antarctic The Antarctic The Sentinel |
genre |
Antarc* Antarctic Antarctica |
genre_facet |
Antarc* Antarctic Antarctica |
op_doi |
https://doi.org/10.7488/era/920 |
_version_ |
1766264194679701504 |