Sea Ice Type Classification Of Sar Imagery

Wackerman, C.; Jentz, R.R.; Shuchman, Robert A.

doi:10.1109/igarss.1988.570157

Cited by 9 publications

(1 citation statement)

References 3 publications

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“…Ice in the vicinity of recognizable features was also identified as to type, concentration and mixture. This information has been used for the development of SAR interpretation algorithms [Shuchman et al, 1989;Wackerman et al, 1988].…”

Section: Figure 2 Is a Sar Mosaic Of An Area Of The Ice In Frammentioning

confidence: 99%

Microwave and physical properties of sea ice in the winter Marginal Ice Zone

Tucker¹,

Grenfell²,

Onstott³

et al. 1991

J. Geophys. Res.

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Surface‐based active and passive microwave measurements were made in conjunction with ice property measurements for several distinct ice types in the Fram Strait during March and April 1987. Synthetic aperture radar imagery downlinked from an aircraft was used to select study sites. The surface‐based radar scattering cross section and emissivity spectra generally support previously inferred qualitative relationships between ice types, exhibiting expected separation between young, first‐year and multiyear ice. Gradient ratios, calculated for both active and passive data, appear to allow clear separation of ice types when used jointly. Surface flooding of multiyear floes, resulting from excessive loading and perhaps wave action, causes both active and passive signatures to resemble those of first‐year ice. This effect could possibly cause estimates of ice type percentages in the marginal ice zone to be in error when derived from aircraft‐ or satellite‐borne sensors.

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Section: Figure 2 Is a Sar Mosaic Of An Area Of The Ice In Frammentioning

confidence: 99%

Microwave and physical properties of sea ice in the winter Marginal Ice Zone

Tucker¹,

Grenfell²,

Onstott³

et al. 1991

J. Geophys. Res.

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Sea ice

Springer Praxis Books

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Identification of sea ice types in spaceborne synthetic aperture radar data

Rignot²,

et al. 1992

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An approach for identification of sea ice types in spaceborne synthetic aperture radar (SAR) image data is presented. The unsupervised classification approach involves cluster analysis for segmentation of the image data followed by cluster labeling based on previously defined look-up tables containing the expected backscatter signatures of different ice types measured by land-based scatterometer. The particular look-up table used for labeling a segmented image is selected based on the seasonal and meteorological conditions at the time of data acquisition. The extensive scatterometer observations and experience accumulated in field campaigns during the last 10 years were used to construct these look-up tables. These tables are expected to evolve as sea ice observations from the European ERS-1 SAR become available. This paper presents the classification approach, its expected performance, the dependence of this performance on radar system performance, and expected ice scattering characteristics. Results using both aircraft and simulated ERS-1 SAR data are presented. The results are compared to limited field ice property measurements and coincident passive microwave imagery. An algorithm based on this experimental approach has been implemented in the geophysical processor system at the Alaska SAR Facility for classification of sea ice data in ERS-1 C band SAR data. The importance of an integrated postlaunch program for validation and improvement of this approach is discussed. INTRODUCTIONThe derivation of valuable information on sea ice properties from radar imagery has increased steadily over the last decade [Carsey, 1989] These SAR studies of sea ice have examined imagery obtained from aircraft and spaceborne SAR systems, usually in combination with other sensors, in situ measurements of ice and snow conditions, and near-surface scatterometer and radiometer measurements. The radars have operated over a wide range of frequencies, incidence angles, and polarizations. During this decade, single-channel spaceborne S ARs are to be launched on the European ERS-1 in 1991, the Japanese ERS-1 in 1992, and the Canadian RADARSAT in 1994. These satellites will provide the first opportunities for the extensive spaceborne monitoring of the polar regions with a SAR since Seasat (which operated for 3• months in 1978). At the end of this decade, NASA has proposed to launch the EOS (Earth Observing System) SAR (a multifrequency, multipolarization SAR) as an integral component of the Mission to Planet Earth, a comprehensive suite of satellite instruments designed to examine global climate change, of which sea ice is a key and supposedly dramatic indicator.In response to these opportunities for examining the polar regions with high-resolution, all-weather spaceborne SARs, the Alaska SAR Facility (ASF) has been implemented at the University of Alaska, Fairbanks, to receive, process, and archive SAR data from these satellites and to generate sea ice geophysical products from the data [ This paper focuses on the ice classification algo...

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Sea Ice Type Classification Of Sar Imagery

Cited by 9 publications

References 3 publications

Microwave and physical properties of sea ice in the winter Marginal Ice Zone

Microwave and physical properties of sea ice in the winter Marginal Ice Zone

Sea ice

Identification of sea ice types in spaceborne synthetic aperture radar data

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