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Advanced Photogrammetry to Assess Lichen Colonization in the Hyper-arid Namib Desert

Hinchliffe, G; Bollard-Breen, B; Cowan, DA; Doshi, A; Gillman, LN; Rios-Murillo, A; Maggs-Kolling, G; Pointing, SB
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http://hdl.handle.net/10292/12472
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Abstract
The hyper-arid central region of the Namib Desert is characterised by quartz desert pavement terrain that is devoid of vascular plant covers. In this extreme habitat the only discernible surface covers are epilithic lichens that colonise exposed surfaces of quartz rocks. These lichens are highly susceptible to disturbance and so field surveys have been limited due to concerns about disturbing this unusual desert feature. Here we present findings that illustrate how non-destructive surveys based upon advanced photogrammetry techniques can yield meaningful and novel scientific data on these lichens. We combined ‘structure from motion analysis’, computer vision and GIS to create 3-dimensional point clouds from two-dimensional imagery. The data were robust in its application to estimating absolute lichen cover. An orange Stellarangia spp. assemblage had coverage of 22.8% of available substrate, whilst for a black Xanthoparmelia spp. assemblage coverage was markedly lower at 0.6% of available substrate. Hyperspectral signatures for both lichens were distinct in the near-infra red range indicating that Xanthoparmelia spp. was likely under relatively more moisture stress than Stellarangia spp. at the time of sampling, and we postulate that albedo effects may have contributed to this in the black lichen. Further transformation of the data revealed a colonisation preference for west-facing quartz surfaces and this coincides with prevailing winds for marine fog that is the major source of moisture in this system. Furthermore, a three-dimensional ‘fly through’ of the lichen habitat was created to illustrate how the application of computer vision in microbiology has further potential as a research and education tool. We discuss how advanced photogrammetry could be applied in astrobiology using autonomous rovers to add quantitative ecological data for visible surface colonisation on the surface of Mars.
Keywords
Astrobiology; Computer vision; Desert; GIS; Lichen; Microbial ecology; Namib Desert; Photogrammetry
Date
October 27, 2017
Source
Frontiers in Microbiology, 8:2083. doi: 10.3389/fmicb.2017.02083
Item Type
Journal Article
Publisher
Frontiers Media
DOI
10.3389/fmicb.2017.02083
Publisher's Version
https://www.frontiersin.org/articles/10.3389/fmicb.2017.02083/full#h6
Rights Statement
© 2017 Hinchliffe, Bollard-Breen, Cowan, Doshi, Gillman, Maggs-Kolling, de Los Rios and Pointing. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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