A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)
(2017) In Izvestiya - Atmospheric and Ocean Physics 53(9). p.1164-1173- Abstract
The tundra–taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra–taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra–taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their... (More)
The tundra–taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra–taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra–taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.
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- author
- Mikheeva, A. I. LU ; Tutubalina, O. V. ; Zimin, M. V. and Golubeva, E. I.
- publishing date
- 2017-12-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- spectral unmixing, subpixel classification, Terra ASTER, treeline, tundra–taiga ecotone, vegetation
- in
- Izvestiya - Atmospheric and Ocean Physics
- volume
- 53
- issue
- 9
- pages
- 10 pages
- publisher
- Pleiades Publishing
- external identifiers
-
- scopus:85042210483
- ISSN
- 0001-4338
- DOI
- 10.1134/S0001433817090213
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2017, Pleiades Publishing, Ltd.
- id
- 5598b783-2e40-423d-a07e-590914781a91
- date added to LUP
- 2024-07-01 10:38:33
- date last changed
- 2025-04-04 15:31:03
@article{5598b783-2e40-423d-a07e-590914781a91,
abstract = {{<p>The tundra–taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra–taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra–taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.</p>}},
author = {{Mikheeva, A. I. and Tutubalina, O. V. and Zimin, M. V. and Golubeva, E. I.}},
issn = {{0001-4338}},
keywords = {{spectral unmixing; subpixel classification; Terra ASTER; treeline; tundra–taiga ecotone; vegetation}},
language = {{eng}},
month = {{12}},
number = {{9}},
pages = {{1164--1173}},
publisher = {{Pleiades Publishing}},
series = {{Izvestiya - Atmospheric and Ocean Physics}},
title = {{A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)}},
url = {{http://dx.doi.org/10.1134/S0001433817090213}},
doi = {{10.1134/S0001433817090213}},
volume = {{53}},
year = {{2017}},
}