Sea ice concentration estimation from Sentinel-1 Synthetic Aperture Radar images over the Fram Strait
Paper in proceeding, 2016

© 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.

Arctic

Autocorrelation

Cross-polarization

Sentinel-1

Sea Ice Concentration

Author

Wiebke Aldenhoff

Chalmers, Earth and Space Sciences, Radar Remote Sensing

Anders Berg

Chalmers, Earth and Space Sciences, Radar Remote Sensing

Leif Eriksson

Chalmers, Earth and Space Sciences, Radar Remote Sensing

36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016; Beijing; China; 10-15 July 2016

Vol. 2016-November Art no 7731001, Pages 7675-7677

Radar remote sensing of sea ice in the Polar regions

Swedish National Space Board (140/13), 2014-01-01 -- 2016-12-31.

Areas of Advance

Transport

Subject Categories

Remote Sensing

Oceanography, Hydrology, Water Resources

Roots

Basic sciences

DOI

10.1109/IGARSS.2016.7731001

More information

Latest update

6/11/2020