Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations

Manual ice charting from multi-sensor satellite data analysis has for many years been the primary method at the National Ice Services for producing sea ice information for marine safety. Ice analysts primarily use satellite synthetic aperture radar (SAR) imagery due to the high spatial resolution an...

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Main Authors: Wulf, Tore, Kreiner, Matilde Brandt, Buus-Hinkler, Jørgen, Tonboe, Rasmus T., Høyer, Jacob L., Saldo, Roberto, Pedersen, Leif Toudal, Nielsen, Allan Aasbjerg, Skriver, Henning, Malmgren-Hansen, David
Format: Conference Object
Language:English
Published: 2021
Subjects:
Online Access:https://orbit.dtu.dk/en/publications/975b6977-2d02-4834-be6e-70de49dcebd6
https://backend.orbit.dtu.dk/ws/files/255059699/Abstract_CIMRops2science.pdf
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spelling ftdtupubl:oai:pure.atira.dk:publications/975b6977-2d02-4834-be6e-70de49dcebd6 2023-12-24T10:14:17+01:00 Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations Wulf, Tore Kreiner, Matilde Brandt Buus-Hinkler, Jørgen Tonboe, Rasmus T. Høyer, Jacob L. Saldo, Roberto Pedersen, Leif Toudal Nielsen, Allan Aasbjerg Skriver, Henning Malmgren-Hansen, David 2021 application/pdf https://orbit.dtu.dk/en/publications/975b6977-2d02-4834-be6e-70de49dcebd6 https://backend.orbit.dtu.dk/ws/files/255059699/Abstract_CIMRops2science.pdf eng eng https://orbit.dtu.dk/en/publications/975b6977-2d02-4834-be6e-70de49dcebd6 info:eu-repo/semantics/openAccess Wulf , T , Kreiner , M B , Buus-Hinkler , J , Tonboe , R T , Høyer , J L , Saldo , R , Pedersen , L T , Nielsen , A A , Skriver , H & Malmgren-Hansen , D 2021 , ' Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations ' , From Science to Operations for the Copernicus Imaging Microwave Radiometer (CIMR) Mission , Noordwijk , Netherlands , 15/04/2020 - 17/04/2020 . /dk/atira/pure/sustainabledevelopmentgoals/responsible_consumption_and_production name=SDG 12 - Responsible Consumption and Production /dk/atira/pure/sustainabledevelopmentgoals/life_below_water name=SDG 14 - Life Below Water conferenceObject 2021 ftdtupubl 2023-11-30T00:06:00Z Manual ice charting from multi-sensor satellite data analysis has for many years been the primary method at the National Ice Services for producing sea ice information for marine safety. Ice analysts primarily use satellite synthetic aperture radar (SAR) imagery due to the high spatial resolution and the capability to image the surface through clouds and in polar darkness, but also optical imagery in clear sky and daylight conditions, thermal-infrared and microwave radiometer data from e.g. AMSR2. Ice analysts mention the spatial resolution of microwave radiometers as the primarily limitation to use the data. The traditional manual ice charting method is time-consuming and limited in spatial and temporal coverage. Further, it is challenged by an increasing amount of available satellite imagery, along with a growing number of users accessing wider parts of the Arctic due to the thinning of the Arctic sea ice. The automation of the time-consuming and labour-intensive sea ice charting process has potential to provide users with near-real time sea ice products of higher spatial resolution, larger spatial and temporal coverage, and increased consistency. To automate the generation of sea ice information from satellite imagery we use a Convolutional Neural Network (CNN) designed for prediction of sea ice in Greenland waters. Automating the process on SAR data alone is challenging. SAR images show patterns related to ice formations, but backscatter intensities can be ambiguous, which complicates the discrimination between ice and open water, e.g. at high wind speeds. Our CNN model tackles the challenges by fusing Sentinel-1 active microwave (SAR) data with Microwave Radiometer (MWR) data from AMSR2 to exploit the advantages of both instruments. While SAR data has ambiguities, it has a very high spatial resolution, whereas MWR data has good contrast between open water and ice. However, the coarse resolution of the AMSR2 MWR observations introduces a new set of obstacles, e.g. land spill-over, which can lead to erroneous ... Conference Object Arctic Greenland Sea ice Technical University of Denmark: DTU Orbit Arctic Greenland
institution Open Polar
collection Technical University of Denmark: DTU Orbit
op_collection_id ftdtupubl
language English
topic /dk/atira/pure/sustainabledevelopmentgoals/responsible_consumption_and_production
name=SDG 12 - Responsible Consumption and Production
/dk/atira/pure/sustainabledevelopmentgoals/life_below_water
name=SDG 14 - Life Below Water
spellingShingle /dk/atira/pure/sustainabledevelopmentgoals/responsible_consumption_and_production
name=SDG 12 - Responsible Consumption and Production
/dk/atira/pure/sustainabledevelopmentgoals/life_below_water
name=SDG 14 - Life Below Water
Wulf, Tore
Kreiner, Matilde Brandt
Buus-Hinkler, Jørgen
Tonboe, Rasmus T.
Høyer, Jacob L.
Saldo, Roberto
Pedersen, Leif Toudal
Nielsen, Allan Aasbjerg
Skriver, Henning
Malmgren-Hansen, David
Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations
topic_facet /dk/atira/pure/sustainabledevelopmentgoals/responsible_consumption_and_production
name=SDG 12 - Responsible Consumption and Production
/dk/atira/pure/sustainabledevelopmentgoals/life_below_water
name=SDG 14 - Life Below Water
description Manual ice charting from multi-sensor satellite data analysis has for many years been the primary method at the National Ice Services for producing sea ice information for marine safety. Ice analysts primarily use satellite synthetic aperture radar (SAR) imagery due to the high spatial resolution and the capability to image the surface through clouds and in polar darkness, but also optical imagery in clear sky and daylight conditions, thermal-infrared and microwave radiometer data from e.g. AMSR2. Ice analysts mention the spatial resolution of microwave radiometers as the primarily limitation to use the data. The traditional manual ice charting method is time-consuming and limited in spatial and temporal coverage. Further, it is challenged by an increasing amount of available satellite imagery, along with a growing number of users accessing wider parts of the Arctic due to the thinning of the Arctic sea ice. The automation of the time-consuming and labour-intensive sea ice charting process has potential to provide users with near-real time sea ice products of higher spatial resolution, larger spatial and temporal coverage, and increased consistency. To automate the generation of sea ice information from satellite imagery we use a Convolutional Neural Network (CNN) designed for prediction of sea ice in Greenland waters. Automating the process on SAR data alone is challenging. SAR images show patterns related to ice formations, but backscatter intensities can be ambiguous, which complicates the discrimination between ice and open water, e.g. at high wind speeds. Our CNN model tackles the challenges by fusing Sentinel-1 active microwave (SAR) data with Microwave Radiometer (MWR) data from AMSR2 to exploit the advantages of both instruments. While SAR data has ambiguities, it has a very high spatial resolution, whereas MWR data has good contrast between open water and ice. However, the coarse resolution of the AMSR2 MWR observations introduces a new set of obstacles, e.g. land spill-over, which can lead to erroneous ...
format Conference Object
author Wulf, Tore
Kreiner, Matilde Brandt
Buus-Hinkler, Jørgen
Tonboe, Rasmus T.
Høyer, Jacob L.
Saldo, Roberto
Pedersen, Leif Toudal
Nielsen, Allan Aasbjerg
Skriver, Henning
Malmgren-Hansen, David
author_facet Wulf, Tore
Kreiner, Matilde Brandt
Buus-Hinkler, Jørgen
Tonboe, Rasmus T.
Høyer, Jacob L.
Saldo, Roberto
Pedersen, Leif Toudal
Nielsen, Allan Aasbjerg
Skriver, Henning
Malmgren-Hansen, David
author_sort Wulf, Tore
title Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations
title_short Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations
title_full Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations
title_fullStr Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations
title_full_unstemmed Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations
title_sort fusion of satellite sar and passive microwave radiometer data for automated sea ice mapping and the expected impact of cimr observations
publishDate 2021
url https://orbit.dtu.dk/en/publications/975b6977-2d02-4834-be6e-70de49dcebd6
https://backend.orbit.dtu.dk/ws/files/255059699/Abstract_CIMRops2science.pdf
geographic Arctic
Greenland
geographic_facet Arctic
Greenland
genre Arctic
Greenland
Sea ice
genre_facet Arctic
Greenland
Sea ice
op_source Wulf , T , Kreiner , M B , Buus-Hinkler , J , Tonboe , R T , Høyer , J L , Saldo , R , Pedersen , L T , Nielsen , A A , Skriver , H & Malmgren-Hansen , D 2021 , ' Fusion of satellite SAR and passive microwave radiometer data for automated sea ice mapping and the expected impact of CIMR observations ' , From Science to Operations for the Copernicus Imaging Microwave Radiometer (CIMR) Mission , Noordwijk , Netherlands , 15/04/2020 - 17/04/2020 .
op_relation https://orbit.dtu.dk/en/publications/975b6977-2d02-4834-be6e-70de49dcebd6
op_rights info:eu-repo/semantics/openAccess
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