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Sea ice concentration estimation from Sentinel-1 Synthetic Aperture Radar images over the Fram Strait

Wiebke Aldenhoff (Institutionen för rymd- och geovetenskap, Radarfjärranalys) ; Anders Berg (Institutionen för rymd- och geovetenskap, Radarfjärranalys) ; Leif E.B. Eriksson (Institutionen för rymd- och geovetenskap, Radarfjärranalys)
36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016; Beijing; China; 10-15 July 2016 Vol. 2016-November (2016), p. Art no 7731001, Pages 7675-7677.
[Konferensbidrag, refereegranskat]

© 2016 IEEE.In this paper we present an algorithm for sea ice concentration estimation in the Arctic from C-band dual polarization Sentinel-1A SAR images. The algorithm is based on spatial autocorrelation and utilizes an artificial neural network to map the image information to sea ice concentration. The cross-polarization channel facilitates the improvement of concentration estimates of images with high backscatter over open water in the normally used co-polarization channel. Ice charts from the Norwegian meteorological institute are used for the training of the network and as a reference. A mean absolute error of 14.55 (ice concentration is given in the range from 0 to 100) of a test data set consisting of 20 images underlines the capabilities of the proposed algorithm.

Nyckelord: Arctic , Autocorrelation , Cross-polarization , Sea Ice Concentration , Sentinel-1

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Denna post skapades 2017-01-20. Senast ändrad 2017-03-31.
CPL Pubid: 247513


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Institutionen för rymd- och geovetenskap, Radarfjärranalys (2010-2017)



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Sea Ice Concentration Estimation and Ice Type Classification from Dual-Frequency Satellite Synthetic Aperture Radar