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Record #118256:

SAR image classification of ice in the Gulf of Bothnia / Y. Sun, A. Carlström, Jan Askne.

Title: SAR image classification of ice in the Gulf of Bothnia / Y. Sun, A. Carlström, Jan Askne.
Author(s): Sun, Y.
Carlström, A.
Askne, Jan.
Date: 1992.
In: International Journal of Remote Sensing. (1992.), Vol. 13(13) (1992)
Abstract: Develops and compares pixel-based and region-based approaches to sea-ice classification, using airborne synthetic aperture radar imagery together with air photography for reference. Pixel-based approach is based on adaptive filtering, whereas region-based is based on segmentation using edge detection with region growing algorithm. Latter gave better result. For case study, accuracy of 80% was obtained when classifying SAR image into four groups (open water, level ice, brash ice, rubble fields). Accuracy of 90% obtained for three groups, combining brash and rubble.
Notes:

International Journal of Remote Sensing. Vol. 13(13) :2489-2514 (1992).

Keywords: 551.32 -- Glaciology.
551.326 -- Floating ice.
551.326.7 -- Sea ice.
551.326.022 -- Floating ice, airborne sensing.
629.783 -- Satellites.
53.087.23 -- Remote sensing.
621.396.96 -- Radar.
551.326.3 -- Floating ice, structure and surface features.
001.4 -- Nomenclature and terminology.
001.89 -- Research programmes: Bothnian Experiment in Preparation for ERS-1 (BEPERS).
E6 -- Glaciology: floating ice.
(*60) -- Arctic Ocean and adjacent waters.
(*611) -- Baltic Sea.
SPRI record no.: 118256

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245 10 ‡aSAR image classification of ice in the Gulf of Bothnia /‡cY. Sun, A. Carlström, Jan Askne.
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300 ## ‡ap. 2489-2514 :‡bill., diags., tables.
500 ## ‡aInternational Journal of Remote Sensing. Vol. 13(13) :2489-2514 (1992).
520 3# ‡aDevelops and compares pixel-based and region-based approaches to sea-ice classification, using airborne synthetic aperture radar imagery together with air photography for reference. Pixel-based approach is based on adaptive filtering, whereas region-based is based on segmentation using edge detection with region growing algorithm. Latter gave better result. For case study, accuracy of 80% was obtained when classifying SAR image into four groups (open water, level ice, brash ice, rubble fields). Accuracy of 90% obtained for three groups, combining brash and rubble.
650 07 ‡a551.32 -- Glaciology.‡2udc
650 07 ‡a551.326 -- Floating ice.‡2udc
650 07 ‡a551.326.7 -- Sea ice.‡2udc
650 07 ‡a551.326.022 -- Floating ice, airborne sensing.‡2udc
650 07 ‡a629.783 -- Satellites.‡2udc
650 07 ‡a53.087.23 -- Remote sensing.‡2udc
650 07 ‡a621.396.96 -- Radar.‡2udc
650 07 ‡a551.326.3 -- Floating ice, structure and surface features.‡2udc
650 07 ‡a001.4 -- Nomenclature and terminology.‡2udc
650 07 ‡a001.89 -- Research programmes: Bothnian Experiment in Preparation for ERS-1 (BEPERS).‡2udc
650 07 ‡aE6 -- Glaciology: floating ice.‡2local
651 #7 ‡a(*60) -- Arctic Ocean and adjacent waters.‡2udc
651 #7 ‡a(*611) -- Baltic Sea.‡2udc
700 1# ‡aCarlström, A.
700 1# ‡aAskne, Jan.
773 0# ‡7nnas ‡tInternational Journal of Remote Sensing. ‡gVol. 13(13) (1992) ‡wSPRI-1038
917 ## ‡aUnenhanced record from Muscat, imported 2019
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