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Linear spectral mixture modelling of arctic vegetation using ground spectroradiometry

Published online by Cambridge University Press:  29 November 2011

Anna Mikheeva ,
Anton Novichikhin  and
Olga Tutubalina
Anna Mikheeva
Affiliation:
Faculty of Geography, M.V. Lomonosov Moscow State University, Leninskiye Gory, Moscow, 119991, Russia (Arvin2@yandex.ru)
Anton Novichikhin
Affiliation:
Faculty of Geography, M.V. Lomonosov Moscow State University, Leninskiye Gory, Moscow, 119991, Russia (Arvin2@yandex.ru)
Olga Tutubalina
Affiliation:
Faculty of Geography, M.V. Lomonosov Moscow State University, Leninskiye Gory, Moscow, 119991, Russia (Arvin2@yandex.ru)
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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.

Type
Research Article
Information
Polar Record , Volume 48 , Special Issue 1: Papers from the 11th Circumpolar Remote Sensing Symposium , January 2012 , pp. 63 - 74
Copyright
Copyright © Cambridge University Press 2011

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