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Remote Sens. 2016, 8(10), 856;

Spectral Discrimination of Vegetation Classes in Ice-Free Areas of Antarctica

Department of Ecology and Animal Biology, University of Vigo, School of Sciences, Campus Lagoas-Marcosende, Vigo 36310, Spain
Department of Signal Theory and Communications, University of Vigo, AtlantTIC Research Center, Vigo 36310, Spain
Author to whom correspondence should be addressed.
Academic Editors: Yuei-An Liou, Chyi-Tyi Lee, Yuriy Kuleshov, Jean-Pierre Barriot, Chung-Ru Ho, Randolph H. Wynne and Prasad S. Thenkabail
Received: 4 July 2016 / Revised: 21 September 2016 / Accepted: 11 October 2016 / Published: 18 October 2016
(This article belongs to the Special Issue Earth Observations for a Better Future Earth)
PDF [32996 KB, uploaded 18 October 2016]


Detailed monitoring of vegetation changes in ice-free areas of Antarctica is crucial to determine the effects of climate warming and increasing human presence in this vulnerable ecosystem. Remote sensing techniques are especially suitable in this distant and rough environment, with high spectral and spatial resolutions needed owing to the patchiness and similarity between vegetation elements. We analyze the reflectance spectra of the most representative vegetation elements in ice-free areas of Antarctica to assess the potential for discrimination. This research is aimed as a basis for future aircraft/satellite research for long-term vegetation monitoring. The study was conducted in the Barton Peninsula, King George Island. The reflectance of ground patches of different types of vegetation or bare ground (c. 0.25 m 2 , n = 30 patches per class) was recorded with a spectrophotometer measuring between 340 nm to 1025 nm at a resolution of 0.38 n m . We used Linear Discriminant Analysis (LDA) to classify the cover classes according to reflectance spectra, after reduction of the number of bands using Principal Component Analysis (PCA). The first five principal components explained an accumulated 99.4% of the total variance and were added to the discriminant function. The LDA classification resulted in c. 92% of cases correctly classified (a hit ratio 11.9 times greater than chance). The most important region for discrimination was the visible and near ultraviolet (UV), with the relative importance of spectral bands steeply decreasing in the Near Infra-Red (NIR) region. Our study shows the feasibility of discriminating among representative taxa of Antarctic vegetation using their spectral patterns in the near UV, visible and NIR. The results are encouraging for hyperspectral vegetation mapping in Antarctica, which could greatly facilitate monitoring vegetation changes in response to a changing environment, reducing the costs and environmental impacts of field surveys. View Full-Text
Keywords: Antarctica; classification; field spectroscopy; hyperspectral imaging; species discrimination; lichen; moss; Deschampsia antarctica Antarctica; classification; field spectroscopy; hyperspectral imaging; species discrimination; lichen; moss; Deschampsia antarctica

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Calviño-Cancela, M.; Martín-Herrero, J. Spectral Discrimination of Vegetation Classes in Ice-Free Areas of Antarctica. Remote Sens. 2016, 8, 856.

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