Mapping lichen distribution on the Antarctic Peninsula using remote sensing, lichen spectra and photographic documentation by citizen scientists

Casanovas, Paula; Black, Martin ORCID: https://orcid.org/0000-0003-2424-5726; Fretwell, Peter ORCID: https://orcid.org/0000-0002-1988-5844; Convey, Peter ORCID: https://orcid.org/0000-0001-8497-9903. 2015 Mapping lichen distribution on the Antarctic Peninsula using remote sensing, lichen spectra and photographic documentation by citizen scientists. Polar Research, 34, 25633. 8, pp. 10.3402/polar.v34.25633

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Abstract/Summary

On the Antarctic Peninsula, lichens are the most diverse botanical component of the terrestrial ecosystem. However, detailed information on the distribution of lichens on the Antarctic Peninsula region is scarce, and the data available exhibit significant heterogeneity in sampling frequency and effort. Satellite remote sensing, in particular the use of the Normalized Difference Vegetation Index (NDVI), has facilitated determination of vegetation richness and cover distribution in some remote and otherwise inaccessible environments. However, it is known that using NDVI for the detection of vegetation can overlook the presence of lichens even if their land cover is extensive. We tested the use of known spectra of lichens in a matched filtering technique for the detection and mapping of lichen-covered land from remote sensing imagery on the Antarctic Peninsula, using data on lichen presence collected by citizen scientists and other non-specialists as ground truthing. Our results confirm that the use of this approach allows for the detection of lichen flora on the Antarctic Peninsula, showing an improvement over the use of NDVI alone for the mapping of flora in this area

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.3402/polar.v34.25633
Programmes:	BAS Programmes > Polar Science for Planet Earth (2009 - ) > Ecosystems BAS Programmes > Polar Science for Planet Earth (2009 - ) > Environmental Change and Evolution BAS Programmes > BAS Corporate
ISSN:	0800-0395
Additional Keywords:	Antarctica, NDVI, matched filtering, Landsat, remote sensing
Date made live:	27 Oct 2015 09:47 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/508000

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