Science Service System

Summary of Proposal OCE2363

TitleScientific evaluation of retrieval of small-scale sea ice features by using very high-resolution SAR imagery
Investigator Hwang, Byongjun - The Scottish Association for Marine Science, Sea ice
Team Members
Mr Krishfield, Richard - Woods Hole Oceanographic Institution, Woods Hole Oceanographic Institution
Prof Kim, Duk-Jin - Seoul National University, School of Earth and Environmental Sciences (SEES)
Dr. Ren, Jinchang - University of Strathclyde, Centre for excellence in Signal and Image Processing (CeSIP)
Dr Polashenski, Chris - Cold Regions Research and Engineering Laboratory Alaska Projects Office, Cold Regions Research and Engineering Laboratory Alaska Projects Office
SummaryThe objective of this project is twofold. First is to examine the correlation between TerraSAR-X SAR data and ice thickness (and type). This is motivated by recent availability of super high-resolution ST imagery as well as the study done by Krishfield et al. (2014, JGR in press). In the study they explore the correlation between coarse resolution (about 10 km) passive microwave radiometer AMSR-E data and ice thickness (draft) measured from the upward looking sonar (ULS) moorings. Despite significant discrepancy in resolution between AMSR-E and ULS measurements, the results showed some correlation during winter months. In this project we propose to investigate this further into SAR data, in order to examine whether correlation exists between SAR and ice thickness data. We examine the correlation in many different parameters from both ST and SM images, collocated with the ULS ice thickness measurements. The second objective is to investigate variability of small-scale sea ice features during both winter and summer months, and how such variability associated with ice thickness (and type). For example how thinner first-year ice is different from thicker multiyear ice in terms of amount of leads, ridges, melt ponds and floe size. As the Arctic Ocean undergoes changes from thicker multiyear ice to thinner first-year ice, understanding how small-scale ice features vary according to ice thickness (and type) is an important question. To achieve these objectives we have four specific tasks, a) retrieval of small-scale sea ice features, b) analysis of sea ice feature statistics with ice thickness data, c) comparison of small-scale features between super high-resolution ST and SM imagery, and d) correlation analysis between SAR data and ice thickness. These tasks requires about four months of TerraSAR-X ST and SM images (about 240 images) during two years of period. Expected deliverable include small-scale feature data derived from both ST and SM images, interim and final reports that contain correlation analysis and statistical analysis of small-scale features as a function of ice thickness and type. Funding for the staff time required in this project has been secured through projects funded from EU, US Office of Naval Research (ONR), and UK NERC.

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DLR 2004-2016