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A comparison of two 85-GHz SSM/I ice concentration algorithms with AVHRR and ERS-2 SAR imagery

TitleA comparison of two 85-GHz SSM/I ice concentration algorithms with AVHRR and ERS-2 SAR imagery
Publication TypeJournal Article
Year of Publication2003
AuthorsKern, S., L. Kaleschke, and D. A. Clausi
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume41
Pagination2294 - 2306
ISSN0196-2892
Keywords85 GHz, Advanced Very High Resolution Radiometer data, ARTIST sea ice algorithm, ASI, AVHRR imagery, brightness temperatures, Greenland Sea, ice-type classes, oceanographic techniques, radar imaging, remote sensing by radar, SAR imagery, sea ice, SEA LION algorithm, SLA, spaceborne imagery, spaceborne radar, Special Sensor Microwave/Imager data, Spring, SSM/I ice concentration algorithms, synthetic aperture radar, texture
Abstract

Sea ice concentrations obtained with two algorithms from Special Sensor Microwave/Imager (SSM/I) data are compared to spaceborne visible/infrared and active microwave imagery for the Greenland Sea in spring. Both algorithms, the ARTIST Sea Ice algorithm (ASI) and the SEA LION algorithm (SLA), utilize 85-GHz SSM/I brightness temperatures with a spatial resolution of 15 km times;13 km. Ice concentrations obtained from Advanced Very High Resolution Radiometer (AVHRR) infrared data in cloud-free areas are underestimated by SLA and ASI ice concentrations by 3.6% and 8.3% (correlation coefficients of 0.90 and 0.91). Ice concentrations estimated from texture classified ERS-2 synthetic aperture radar (SAR) images by assigning experience-based ice concentrations to ice-type classes are overestimated by SLA and ASI ice concentrations by 4.4% and 1.5% (correlation coefficients of 0.84 and 0.77). However, omitting low/high ice concentrations forming up to 80% (AVHRR) and 60% (SAR) of the entire dataset reveals a significantly different statistic. For instance, the correlation between AVHRR and SLA and ASI ice concentrations drops to 0.77 and 0.70, respectively. All presented techniques to obtain ice concentrations need improvement and future developments should involve larger datasets. However, with care, both algorithms can be used to obtain reasonable ice concentration maps with a 12.5 km times;12.5 km grid-cell size.

DOI10.1109/TGRS.2003.817181