Paper
21 December 1994 Validation and evaluation of a workstation for monitoring sea ice
Neil McIntyre, Diane Boardman, David Darwin, Ken Sullivan
Author Affiliations +
Abstract
Demand for reliable sea ice information comes from many quarters including ship routing and resource exploitation companies, weather forecasting agencies and glaciological research institution. For operational purposes, this information is typically required for local regions on short timescales. To explore this market a prototype sea ice workstation has been developed. The workstation uses data from several current earth observation sensors, combining the advantages of regional survey, all-weather capability and high-resolution imagery. The output from the workstation is an integrated sea ice chart which can be used to display combinations of ice edge, ice type, ice concentrations, ice motion vectors and sea surface temperatures. During the course of its development significant new progress in automated ice classification has been achieved together with the enhancement of existing ice motion algorithms. The quality of the sea ice information from each geophysical algorithm was assessed through validation campaigns which collected independent datasets. The results of this analysis show the ice type classification to be most accurate in identifying multi-year ice; this is probably the most critical ice category for navigational purposes. A program of end-user evaluation has also been started in which sea ice charts are supplied to operational organizations and value-added services. This will continue during 1994 and provide feedback on the use of the workstation in a semi-operational environment.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Neil McIntyre, Diane Boardman, David Darwin, and Ken Sullivan "Validation and evaluation of a workstation for monitoring sea ice", Proc. SPIE 2319, Oceanic Remote Sensing and Sea Ice Monitoring, (21 December 1994); https://doi.org/10.1117/12.197274
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Cited by 1 scholarly publication.
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KEYWORDS
Synthetic aperture radar

Algorithm development

Sensors

Backscatter

Image classification

Meteorology

Data conversion

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