Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry

ABSTRACT An experimental linear mixture modelling using ground spectroradiometric measurements in the Kola Peninsula, Russia has been carried out to create a basis for mapping vegetation and non-vegetation components in the tundra-taiga ecotone using satellite imagery. We concentrated on the ground...

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Published in:Polar Record
Main Authors: Mikheeva, Anna, Novichikhin, Anton, Tutubalina, Olga
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2011
Subjects:
Online Access:http://dx.doi.org/10.1017/s0032247411000441
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0032247411000441
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spelling crcambridgeupr:10.1017/s0032247411000441 2024-03-03T08:42:03+00:00 Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry Mikheeva, Anna Novichikhin, Anton Tutubalina, Olga 2011 http://dx.doi.org/10.1017/s0032247411000441 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0032247411000441 en eng Cambridge University Press (CUP) https://www.cambridge.org/core/terms Polar Record volume 48, issue 1, page 63-74 ISSN 0032-2474 1475-3057 General Earth and Planetary Sciences Ecology Geography, Planning and Development journal-article 2011 crcambridgeupr https://doi.org/10.1017/s0032247411000441 2024-02-08T08:43:48Z ABSTRACT An experimental linear mixture modelling using ground spectroradiometric measurements in the Kola Peninsula, Russia has been carried out to create a basis for mapping vegetation and non-vegetation components in the tundra-taiga ecotone using satellite imagery. We concentrated on the ground level experiment with the goal to use it further for the classification of multispectral satellite imagery through spectral unmixing. This experiment was performed on the most detailed level of remote sensing research which is free from atmospheric effects and easy to understand. We have measured typical ecotone components, including Cetraria nivalis , Betula tortuosa , Empetrum nigrum, Betula nana, Picea abies and rocks (nepheline syenite). The result of the experiment shows that the spectral mixture is indeed formed linearly but different components have different influence. Typical spectral thresholds for each component were found which are significant for vegetation mapping. Spectral unmixing of ground level data was performed and accuracy was estimated. The results add new information on typical spectral thresholds which can potentially be applied for multispectral satellite imagery when upscaling from high resolution to coarser resolution. Article in Journal/Newspaper Arctic Betula nana Empetrum nigrum kola peninsula Polar Record taiga Tundra Cambridge University Press Arctic Kola Peninsula Polar Record 48 1 63 74
institution Open Polar
collection Cambridge University Press
op_collection_id crcambridgeupr
language English
topic General Earth and Planetary Sciences
Ecology
Geography, Planning and Development
spellingShingle General Earth and Planetary Sciences
Ecology
Geography, Planning and Development
Mikheeva, Anna
Novichikhin, Anton
Tutubalina, Olga
Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry
topic_facet General Earth and Planetary Sciences
Ecology
Geography, Planning and Development
description ABSTRACT An experimental linear mixture modelling using ground spectroradiometric measurements in the Kola Peninsula, Russia has been carried out to create a basis for mapping vegetation and non-vegetation components in the tundra-taiga ecotone using satellite imagery. We concentrated on the ground level experiment with the goal to use it further for the classification of multispectral satellite imagery through spectral unmixing. This experiment was performed on the most detailed level of remote sensing research which is free from atmospheric effects and easy to understand. We have measured typical ecotone components, including Cetraria nivalis , Betula tortuosa , Empetrum nigrum, Betula nana, Picea abies and rocks (nepheline syenite). The result of the experiment shows that the spectral mixture is indeed formed linearly but different components have different influence. Typical spectral thresholds for each component were found which are significant for vegetation mapping. Spectral unmixing of ground level data was performed and accuracy was estimated. The results add new information on typical spectral thresholds which can potentially be applied for multispectral satellite imagery when upscaling from high resolution to coarser resolution.
format Article in Journal/Newspaper
author Mikheeva, Anna
Novichikhin, Anton
Tutubalina, Olga
author_facet Mikheeva, Anna
Novichikhin, Anton
Tutubalina, Olga
author_sort Mikheeva, Anna
title Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry
title_short Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry
title_full Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry
title_fullStr Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry
title_full_unstemmed Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry
title_sort linear spectral mixture modelling of arctic vegetation using ground spectroradiometry
publisher Cambridge University Press (CUP)
publishDate 2011
url http://dx.doi.org/10.1017/s0032247411000441
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0032247411000441
geographic Arctic
Kola Peninsula
geographic_facet Arctic
Kola Peninsula
genre Arctic
Betula nana
Empetrum nigrum
kola peninsula
Polar Record
taiga
Tundra
genre_facet Arctic
Betula nana
Empetrum nigrum
kola peninsula
Polar Record
taiga
Tundra
op_source Polar Record
volume 48, issue 1, page 63-74
ISSN 0032-2474 1475-3057
op_rights https://www.cambridge.org/core/terms
op_doi https://doi.org/10.1017/s0032247411000441
container_title Polar Record
container_volume 48
container_issue 1
container_start_page 63
op_container_end_page 74
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