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Spatial variability in sea-ice algal biomass: an under-ice remote sensing perspective

Citation

Cimoli, E and Meiners, KM and Lund-hansen, LC and Lucieer, V, Spatial variability in sea-ice algal biomass: an under-ice remote sensing perspective, Advances in Polar Science, 28, (4) pp. 268-296. ISSN 1674-9928 (2017) [Refereed Article]


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Copyright Statement

Copyright 2017 Advances in Polar Science

Official URL: http://www.aps-polar.org/paper/2017/28/04/A1805080...

DOI: doi:10.13679/j.advps.2017.4.00268

Abstract

Sea-ice algae are a paramount feature of polar marine ecosystems and ice algal standing stocks are characterized by a high spatio-temporal variability. Traditional sampling techniques, e.g., ice coring, are labor intensive, spatially limited and invasive, thereby limiting our understanding of ice algal biomass variability patterns. This has consequences for quantifying ice-associated algal biomass distribution, primary production, and detecting responses to changing environmental conditions. Close-range under-ice optical remote sensing techniques have emerged as a capable alternative providing non-invasive estimates of ice algal biomass and its spatial variability. In this review we first summarize observational studies, using both classical and new methods that aim to capture biomass variability at multiple spatial scales and identify the environmental drivers. We introduce the complex multi-disciplinary nature of under-ice spectral radiation profiling techniques and discuss relevant concepts of sea-ice radiative transfer and bio-optics. In addition, we tabulate and discuss advances and limitations of different statistical approaches used to correlate biomass and under-ice light spectral composition. We also explore theoretical and technical aspects of using Unmanned Underwater Vehicles (UUV), and Hyperspectral Imaging (HI) technology in an under-ice remote sensing context. The review concludes with an outlook and way forward to combine platforms and optical sensors to quantify ice algal spatial variability and establish relationships with its environmental drivers.

Item Details

Item Type:Refereed Article
Keywords:hyperspectal, seaice, mapping, sea ice, ice algae, spatial variability, biomass, remote sensing, transmittance
Research Division:Engineering
Research Group:Geomatic Engineering
Research Field:Photogrammetry and Remote Sensing
Objective Division:Environment
Objective Group:Ecosystem Assessment and Management
Objective Field:Ecosystem Assessment and Management of Marine Environments
Author:Cimoli, E (Mr Emiliano Cimoli)
Author:Meiners, KM (Dr Klaus Meiners)
Author:Lucieer, V (Dr Vanessa Lucieer)
ID Code:126163
Year Published:2017
Deposited By:Ecology and Biodiversity
Deposited On:2018-05-25
Last Modified:2018-06-04
Downloads:4 View Download Statistics

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