Analysing vegetation changes in continental Antarctica using modern UAV-based technology
In the context of global climate change, changes in vegetation cover have attracted much attention. Antarctica represents an ideal open-air laboratory to do so and the Rudolph plot (120 m * 30 m) created in 1962 originally at Cape Hallett offers a unique long-term research opportunity. In December 2...
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Online Access: | https://hdl.handle.net/1842/37638 https://doi.org/10.7488/era/919 |
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ftunivedinburgh:oai:era.ed.ac.uk:1842/37638 2023-07-30T03:59:26+02:00 Analysing vegetation changes in continental Antarctica using modern UAV-based technology Pan, Yueming Colesie, Claudia 2020-08-20 application/pdf https://hdl.handle.net/1842/37638 https://doi.org/10.7488/era/919 en eng The University of Edinburgh https://hdl.handle.net/1842/37638 http://dx.doi.org/10.7488/era/919 continental Antarctica the Rudolph plot UAV investigation object-based analysis Random Forest vegetation coverage changes Thesis or Dissertation Masters MSc Master of Science 2020 ftunivedinburgh https://doi.org/10.7488/era/919 2023-07-09T20:32:24Z In the context of global climate change, changes in vegetation cover have attracted much attention. Antarctica represents an ideal open-air laboratory to do so and the Rudolph plot (120 m * 30 m) created in 1962 originally at Cape Hallett offers a unique long-term research opportunity. In December 2018, a UAV mission was launched over this region, and the obtained high-resolution RGB image was applied in this study to present the coverage and distribution pattern of algae, lichen and moss according to the object-based classification within a unit of 1 m2 square. The data have been compared to an older data set collected in 2004, allowing to quantitatively assess vegetation change over 15 years. The object-based image analysis had been processed based on the multi-resolution segmentation and Random Forest classification in eCognition. Results showed that the total vegetation-covered area in 2018 was 556.64 m2, accounting for 14.27% of the whole plot, of which moss occupied more than half of the area. And the distribution of vegetation was scattered but mainly concentrated in flat terrain. Compared with the data in 2004, the overall vegetation-coverage had significantly decreased, especially dense vegetation disappeared, but some areas have been newly colonised as well. It could be suggested that such complex changes may be related to regional microenvironmental factors such as water availability. Master Thesis Antarc* Antarctica Edinburgh Research Archive (ERA - University of Edinburgh) Hallett ENVELOPE(170.217,170.217,-72.317,-72.317) Rudolph ENVELOPE(-62.433,-62.433,-64.900,-64.900) Cape Hallett ENVELOPE(170.217,170.217,-72.317,-72.317) |
institution |
Open Polar |
collection |
Edinburgh Research Archive (ERA - University of Edinburgh) |
op_collection_id |
ftunivedinburgh |
language |
English |
topic |
continental Antarctica the Rudolph plot UAV investigation object-based analysis Random Forest vegetation coverage changes |
spellingShingle |
continental Antarctica the Rudolph plot UAV investigation object-based analysis Random Forest vegetation coverage changes Pan, Yueming Analysing vegetation changes in continental Antarctica using modern UAV-based technology |
topic_facet |
continental Antarctica the Rudolph plot UAV investigation object-based analysis Random Forest vegetation coverage changes |
description |
In the context of global climate change, changes in vegetation cover have attracted much attention. Antarctica represents an ideal open-air laboratory to do so and the Rudolph plot (120 m * 30 m) created in 1962 originally at Cape Hallett offers a unique long-term research opportunity. In December 2018, a UAV mission was launched over this region, and the obtained high-resolution RGB image was applied in this study to present the coverage and distribution pattern of algae, lichen and moss according to the object-based classification within a unit of 1 m2 square. The data have been compared to an older data set collected in 2004, allowing to quantitatively assess vegetation change over 15 years. The object-based image analysis had been processed based on the multi-resolution segmentation and Random Forest classification in eCognition. Results showed that the total vegetation-covered area in 2018 was 556.64 m2, accounting for 14.27% of the whole plot, of which moss occupied more than half of the area. And the distribution of vegetation was scattered but mainly concentrated in flat terrain. Compared with the data in 2004, the overall vegetation-coverage had significantly decreased, especially dense vegetation disappeared, but some areas have been newly colonised as well. It could be suggested that such complex changes may be related to regional microenvironmental factors such as water availability. |
author2 |
Colesie, Claudia |
format |
Master Thesis |
author |
Pan, Yueming |
author_facet |
Pan, Yueming |
author_sort |
Pan, Yueming |
title |
Analysing vegetation changes in continental Antarctica using modern UAV-based technology |
title_short |
Analysing vegetation changes in continental Antarctica using modern UAV-based technology |
title_full |
Analysing vegetation changes in continental Antarctica using modern UAV-based technology |
title_fullStr |
Analysing vegetation changes in continental Antarctica using modern UAV-based technology |
title_full_unstemmed |
Analysing vegetation changes in continental Antarctica using modern UAV-based technology |
title_sort |
analysing vegetation changes in continental antarctica using modern uav-based technology |
publisher |
The University of Edinburgh |
publishDate |
2020 |
url |
https://hdl.handle.net/1842/37638 https://doi.org/10.7488/era/919 |
long_lat |
ENVELOPE(170.217,170.217,-72.317,-72.317) ENVELOPE(-62.433,-62.433,-64.900,-64.900) ENVELOPE(170.217,170.217,-72.317,-72.317) |
geographic |
Hallett Rudolph Cape Hallett |
geographic_facet |
Hallett Rudolph Cape Hallett |
genre |
Antarc* Antarctica |
genre_facet |
Antarc* Antarctica |
op_relation |
https://hdl.handle.net/1842/37638 http://dx.doi.org/10.7488/era/919 |
op_doi |
https://doi.org/10.7488/era/919 |
_version_ |
1772810255881732096 |