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Towards improved estimates of sea-ice algal biomass: experimental assessment of hyperspectral imaging cameras for under-ice studies

Authors :
Emiliano Cimoli
Arko Lucieer
Klaus M. Meiners
Lars Chresten Lund-Hansen
Fraser Kennedy
Andrew Martin
Andrew McMinn
Vanessa Lucieer
Source :
Annals of Glaciology, Vol 58, Pp 68-77 (2017)
Publication Year :
2017
Publisher :
Cambridge University Press, 2017.

Abstract

Ice algae are a key component in polar marine food webs and have an active role in large-scale biogeochemical cycles. They remain extremely under-sampled due to the coarse nature of traditional point sampling methods compounded by the general logistical limitations of surveying in polar regions. This study provides a first assessment of hyperspectral imaging as an under-ice remote-sensing method to capture sea-ice algae biomass spatial variability at the ice/water interface. Ice-algal cultures were inoculated in a unique inverted sea-ice simulation tank at increasing concentrations over designated cylinder enclosures and sparsely across the ice/water interface. Hyperspectral images of the sea ice were acquired with a pushbroom sensor attaining 0.9 mm square pixel spatial resolution for three different spectral resolutions (1.7, 3.4, 6.7 nm). Image analysis revealed biomass distribution matching the inoculated chlorophyll a concentrations within each cylinder. While spectral resolutions >6 nm hindered biomass differentiation, 1.7 and 3.4 nm were able to resolve spatial variation in ice algal biomass implying a coherent sensor selection. The inverted ice tank provided a suitable sea-ice analogue platform for testing key parameters of the methodology. The results highlight the potential of hyperspectral imaging to capture sea-ice algal biomass variability at unprecedented scales in a non-invasive way.

Details

Language :
English
ISSN :
02603055 and 17275644
Volume :
58
Database :
Directory of Open Access Journals
Journal :
Annals of Glaciology
Publication Type :
Academic Journal
Accession number :
edsdoj.4d45d4a1cae4d18ac11f2460a7cdf4c
Document Type :
article
Full Text :
https://doi.org/10.1017/aog.2017.6