Application of an underwater hyperspectral imager (UHI) for the study of sea ice algae

Sea ice provides an important habitat for sea ice algae, the main primary producers in sea ice covered ocean areas. In order to reliably estimate sea ice algal distribution and production, it is important to develop remote sensing methods that can provide these estimates with minimal coring. Underwa...

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Bibliographic Details
Main Author: Osanen, Janina
Format: Master Thesis
Language:English
Published: UiT Norges arktiske universitet 2022
Subjects:
Online Access:https://hdl.handle.net/10037/26678
id ftunivtroemsoe:oai:munin.uit.no:10037/26678
record_format openpolar
spelling ftunivtroemsoe:oai:munin.uit.no:10037/26678 2023-05-15T16:36:33+02:00 Application of an underwater hyperspectral imager (UHI) for the study of sea ice algae Osanen, Janina 2022-08-22 https://hdl.handle.net/10037/26678 eng eng UiT Norges arktiske universitet UiT The Arctic University of Norway https://hdl.handle.net/10037/26678 openAccess Copyright 2022 The Author(s) VDP::Mathematics and natural science: 400::Zoology and botany: 480::Marine biology: 497 Sea ice algae Hyperspectral imager Bio-optics BIO-3950 Master thesis Mastergradsoppgave 2022 ftunivtroemsoe 2022-09-07T23:00:16Z Sea ice provides an important habitat for sea ice algae, the main primary producers in sea ice covered ocean areas. In order to reliably estimate sea ice algal distribution and production, it is important to develop remote sensing methods that can provide these estimates with minimal coring. Underwater hyperspectral imagers (UHI) can capture fine-scale variability in the transmitted spectral profile directly below the sea ice-water interface, which then can be related to core-derived chlorophyll a concentration, providing estimates of in situ chl a biomass across spatial scales. The aim of this research was to obtain optimal NDI wavelength combinations for in situ and in vivo surveys using two different approaches – standardized radiance and transmittance and using the resultant model for mapping fine scale (mm) chlorophyll a distribution. Results indicated successful application of laboratory-based NDI-combinations for estimating fine-scale chl a biomass variability in a natural fjord system. Combining the model with O2-based laboratory experiments, fine scale differences in net community production relative chlorophyll a was be estimated for UHI surveys from two contrasting Svalbard fjords, Tempelfjorden and Van Mijenfjorden. Additionally, the effect of accessory pigments, with a focus on fucoxanthin, on bio-optical models was investigated. Master Thesis ice algae Sea ice Svalbard Tempelfjord* Tempelfjorden Van Mijenfjorden University of Tromsø: Munin Open Research Archive Svalbard Van Mijenfjorden ENVELOPE(14.667,14.667,77.717,77.717) Tempelfjorden ENVELOPE(17.076,17.076,78.404,78.404)
institution Open Polar
collection University of Tromsø: Munin Open Research Archive
op_collection_id ftunivtroemsoe
language English
topic VDP::Mathematics and natural science: 400::Zoology and botany: 480::Marine biology: 497
Sea ice algae
Hyperspectral imager
Bio-optics
BIO-3950
spellingShingle VDP::Mathematics and natural science: 400::Zoology and botany: 480::Marine biology: 497
Sea ice algae
Hyperspectral imager
Bio-optics
BIO-3950
Osanen, Janina
Application of an underwater hyperspectral imager (UHI) for the study of sea ice algae
topic_facet VDP::Mathematics and natural science: 400::Zoology and botany: 480::Marine biology: 497
Sea ice algae
Hyperspectral imager
Bio-optics
BIO-3950
description Sea ice provides an important habitat for sea ice algae, the main primary producers in sea ice covered ocean areas. In order to reliably estimate sea ice algal distribution and production, it is important to develop remote sensing methods that can provide these estimates with minimal coring. Underwater hyperspectral imagers (UHI) can capture fine-scale variability in the transmitted spectral profile directly below the sea ice-water interface, which then can be related to core-derived chlorophyll a concentration, providing estimates of in situ chl a biomass across spatial scales. The aim of this research was to obtain optimal NDI wavelength combinations for in situ and in vivo surveys using two different approaches – standardized radiance and transmittance and using the resultant model for mapping fine scale (mm) chlorophyll a distribution. Results indicated successful application of laboratory-based NDI-combinations for estimating fine-scale chl a biomass variability in a natural fjord system. Combining the model with O2-based laboratory experiments, fine scale differences in net community production relative chlorophyll a was be estimated for UHI surveys from two contrasting Svalbard fjords, Tempelfjorden and Van Mijenfjorden. Additionally, the effect of accessory pigments, with a focus on fucoxanthin, on bio-optical models was investigated.
format Master Thesis
author Osanen, Janina
author_facet Osanen, Janina
author_sort Osanen, Janina
title Application of an underwater hyperspectral imager (UHI) for the study of sea ice algae
title_short Application of an underwater hyperspectral imager (UHI) for the study of sea ice algae
title_full Application of an underwater hyperspectral imager (UHI) for the study of sea ice algae
title_fullStr Application of an underwater hyperspectral imager (UHI) for the study of sea ice algae
title_full_unstemmed Application of an underwater hyperspectral imager (UHI) for the study of sea ice algae
title_sort application of an underwater hyperspectral imager (uhi) for the study of sea ice algae
publisher UiT Norges arktiske universitet
publishDate 2022
url https://hdl.handle.net/10037/26678
long_lat ENVELOPE(14.667,14.667,77.717,77.717)
ENVELOPE(17.076,17.076,78.404,78.404)
geographic Svalbard
Van Mijenfjorden
Tempelfjorden
geographic_facet Svalbard
Van Mijenfjorden
Tempelfjorden
genre ice algae
Sea ice
Svalbard
Tempelfjord*
Tempelfjorden
Van Mijenfjorden
genre_facet ice algae
Sea ice
Svalbard
Tempelfjord*
Tempelfjorden
Van Mijenfjorden
op_relation https://hdl.handle.net/10037/26678
op_rights openAccess
Copyright 2022 The Author(s)
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