On the estimation of physical roughness of sea ice in the Canadian Arctic archipelago using synthetic aperture radar

Sea ice surface roughness is a geophysical property which can be defined and quantified on a variety scales, and consequently affects processes across various scales. The sea ice surface roughness influences various mass, gas, and energy fluxes across the ocean-sea ice-atmosphere interface. Utilizin...

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Bibliographic Details
Published in:Canadian Journal of Remote Sensing
Main Author: Cafarella, Silvie
Other Authors: Scharien, Randall
Format: Thesis
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/1828/11081
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spelling ftuvicpubl:oai:dspace.library.uvic.ca:1828/11081 2023-05-15T14:25:55+02:00 On the estimation of physical roughness of sea ice in the Canadian Arctic archipelago using synthetic aperture radar Cafarella, Silvie Scharien, Randall 2019 application/pdf http://hdl.handle.net/1828/11081 English en eng http://hdl.handle.net/1828/11081 Silvie Marie Cafarella, Randall Scharien, Torsten Geldsetzer, Stephen Howell, Christian Haas, Rebecca Segal & Sasha Nasonova (2019) Estimation of Level and Deformed First-Year Sea Ice Surface Roughness in the Canadian Arctic Archipelago from C- and L-Band Synthetic Aperture Radar, Canadian Journal of Remote Sensing, DOI:10.1080/07038992.2019.1647102 Available to the World Wide Web remote sensing sea ice synthetic aperture radar surface roughness Arctic Thesis 2019 ftuvicpubl 2022-05-19T06:13:16Z Sea ice surface roughness is a geophysical property which can be defined and quantified on a variety scales, and consequently affects processes across various scales. The sea ice surface roughness influences various mass, gas, and energy fluxes across the ocean-sea ice-atmosphere interface. Utilizing synthetic aperture radar (SAR) data to understand and map sea ice roughness is an active area of research. This thesis provides new techniques for the estimation of sea ice surface roughness in the Canadian Arctic Archipelago using synthetic aperture radar (SAR). Estimating and isolating sea ice surface properties from SAR imagery is complicated as there are a number of sea ice and sensor properties that influence the backscattered energy. There is increased difficulty in the melting season due to the presence of melt ponds on the surface, which can often inhibit interactions from the sensor to the sea ice surface as shorter microwaves cannot penetrate through the melt water. An object-based image analysis is here used to quantitatively link the winter first-year sea ice surface roughness to C-band RADARSAT-2 and L-band ALOS-2 PALSAR-2 SAR backscatter measured at two periods: winter (pre-melt) and advanced melt. Since the sea ice in our study area, the Canadian Arctic Archipelago, is landfast, the same ice can be imaged using SAR after the surface roughness measurements are established. Strong correlations between winter measured surface roughness, and C- and L-band SAR backscatter acquired during both the winter and advanced melt periods are observed. Results for winter indicate: (1) C-band HH-polarization backscatter is correlated with roughness (r=0.86) at a shallow incidence angle; and (2) L-band HH- and VV-polarization backscatter is correlated with roughness (r=0.82) at a moderate incidence angle. Results for advanced melt indicate: (1) C-band HV/HH polarization ratio is correlated with roughness (r=-0.83) at shallow incidence angle; (2) C-band HH-polarization backscatter is correlated with roughness (r=0.84) ... Thesis Arctic Arctic Archipelago Arctic Canadian Arctic Archipelago Sea ice University of Victoria (Canada): UVicDSpace Arctic Canadian Arctic Archipelago Canadian Journal of Remote Sensing 45 3-4 457 475
institution Open Polar
collection University of Victoria (Canada): UVicDSpace
op_collection_id ftuvicpubl
language English
topic remote sensing
sea ice
synthetic aperture radar
surface roughness
Arctic
spellingShingle remote sensing
sea ice
synthetic aperture radar
surface roughness
Arctic
Cafarella, Silvie
On the estimation of physical roughness of sea ice in the Canadian Arctic archipelago using synthetic aperture radar
topic_facet remote sensing
sea ice
synthetic aperture radar
surface roughness
Arctic
description Sea ice surface roughness is a geophysical property which can be defined and quantified on a variety scales, and consequently affects processes across various scales. The sea ice surface roughness influences various mass, gas, and energy fluxes across the ocean-sea ice-atmosphere interface. Utilizing synthetic aperture radar (SAR) data to understand and map sea ice roughness is an active area of research. This thesis provides new techniques for the estimation of sea ice surface roughness in the Canadian Arctic Archipelago using synthetic aperture radar (SAR). Estimating and isolating sea ice surface properties from SAR imagery is complicated as there are a number of sea ice and sensor properties that influence the backscattered energy. There is increased difficulty in the melting season due to the presence of melt ponds on the surface, which can often inhibit interactions from the sensor to the sea ice surface as shorter microwaves cannot penetrate through the melt water. An object-based image analysis is here used to quantitatively link the winter first-year sea ice surface roughness to C-band RADARSAT-2 and L-band ALOS-2 PALSAR-2 SAR backscatter measured at two periods: winter (pre-melt) and advanced melt. Since the sea ice in our study area, the Canadian Arctic Archipelago, is landfast, the same ice can be imaged using SAR after the surface roughness measurements are established. Strong correlations between winter measured surface roughness, and C- and L-band SAR backscatter acquired during both the winter and advanced melt periods are observed. Results for winter indicate: (1) C-band HH-polarization backscatter is correlated with roughness (r=0.86) at a shallow incidence angle; and (2) L-band HH- and VV-polarization backscatter is correlated with roughness (r=0.82) at a moderate incidence angle. Results for advanced melt indicate: (1) C-band HV/HH polarization ratio is correlated with roughness (r=-0.83) at shallow incidence angle; (2) C-band HH-polarization backscatter is correlated with roughness (r=0.84) ...
author2 Scharien, Randall
format Thesis
author Cafarella, Silvie
author_facet Cafarella, Silvie
author_sort Cafarella, Silvie
title On the estimation of physical roughness of sea ice in the Canadian Arctic archipelago using synthetic aperture radar
title_short On the estimation of physical roughness of sea ice in the Canadian Arctic archipelago using synthetic aperture radar
title_full On the estimation of physical roughness of sea ice in the Canadian Arctic archipelago using synthetic aperture radar
title_fullStr On the estimation of physical roughness of sea ice in the Canadian Arctic archipelago using synthetic aperture radar
title_full_unstemmed On the estimation of physical roughness of sea ice in the Canadian Arctic archipelago using synthetic aperture radar
title_sort on the estimation of physical roughness of sea ice in the canadian arctic archipelago using synthetic aperture radar
publishDate 2019
url http://hdl.handle.net/1828/11081
geographic Arctic
Canadian Arctic Archipelago
geographic_facet Arctic
Canadian Arctic Archipelago
genre Arctic
Arctic Archipelago
Arctic
Canadian Arctic Archipelago
Sea ice
genre_facet Arctic
Arctic Archipelago
Arctic
Canadian Arctic Archipelago
Sea ice
op_relation http://hdl.handle.net/1828/11081
Silvie Marie Cafarella, Randall Scharien, Torsten Geldsetzer, Stephen Howell, Christian Haas, Rebecca Segal & Sasha Nasonova (2019) Estimation of Level and Deformed First-Year Sea Ice Surface Roughness in the Canadian Arctic Archipelago from C- and L-Band Synthetic Aperture Radar, Canadian Journal of Remote Sensing, DOI:10.1080/07038992.2019.1647102
op_rights Available to the World Wide Web
container_title Canadian Journal of Remote Sensing
container_volume 45
container_issue 3-4
container_start_page 457
op_container_end_page 475
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