Vegetation abundance on the Barton Peninsula, Antarctica: Estimation from highresolutionsatellite images
Cited 19 time in
Cited 24 time in
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Title
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Vegetation abundance on the Barton Peninsula, Antarctica: Estimation from highresolutionsatellite images
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Authors
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Shin, Jung-Il
Kim, Hyun-cheol
Kim, Sang-Il
Hong, Soon Gyu
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Subject
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Biodiversity & Conservation; Environmental Sciences & Ecology
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Keywords
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Abundance; Vegetation; Antarctica; Satellite; Spectral mixture analysis
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Issue Date
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2014
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Citation
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Shin, Jung-Il, et al. 2014. "Vegetation abundance on the Barton Peninsula, Antarctica: Estimation from highresolutionsatellite images". Polar Biol, 37: 1579-1588.
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Abstract
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Polar biodiversity should be monitored as an
indicator of climate change. Biodiversity is mainly
observed by field survey although this is very limited in
broad inaccessible polar regions. Satellite imagery may
provide valuable data with less bias, although spatial,
spectral, and temporal resolutions are limited for analyzing
biodiversity. The present study has two objectives. The first
is constructing a first-ever vegetation map of the entire
Barton Peninsula, Antarctica. The second is developing a
monitoring method for long-term variation of vegetation,
based on satellite images. Dominant mosses and lichens are
distributed in small and sparse patches, which are limited
to analysis using high-resolution satellite images. A subpixel
classification method, spectral mixture analysis, is
applied to overcome limited spatial resolution. As a result,
vegetation shows high abundance along the southeastern
shore and low-to-medium abundance in the nearly snowfree
inland area. Even though spatial patterns of vegetation
were almost invariant over 6 years, there was interannual
variation in abundance aspects because of meteorological
conditions. Therefore, extensive and long-term monitoring
is needed for aspects of distribution and abundance. The
present results can be used to design field surveys and
monitor long-term variation as elementary data.
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DOI
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http://dx.doi.org/10.1007/s00300-014-1543-5
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Type
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Article
- Appears in Collections
- 2014-2016, Long-Term Ecological Researches on King George Island to Predict Ecosystem Responses to Climate Change (14-16) / Hong; Soon Gyu (PE14020; PE15020; PE16020)
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