Sea ice concentration estimation techniques using machine learning: an end-to-end workflow for estimating concentration maps from SAR images

2021 ◽  
pp. 319-337
Author(s):  
Stefan Dominicus ◽  
Amit Kumar Mishra ◽  
Christo Rautenbach
Keyword(s):  
Machine Learning ◽  
Sea Ice ◽  
Sar Images ◽  
Sea Ice Concentration ◽  
Estimation Techniques ◽  
Concentration Estimation ◽  
Ice Concentration ◽  
End To End

Prediction of Arctic Sea Ice Concentration of Kara-Barents Seas Using RCM Data with Machine Learning

2017 ◽  
Vol 12 (4) ◽  
pp. 349-365
Author(s):  
Ji-Won Kim ◽  
◽  
Kwang-Jin Kim ◽  
Soo-Jin Lee ◽  
Yeong-Ho Kim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Sea Ice ◽  
Arctic Sea Ice ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Ice Concentration

scholarly journals A sea ice concentration estimation algorithm utilizing radiometer and SAR data

2014 ◽  
Vol 8 (5) ◽  
pp. 1639-1650 ◽  
Author(s):  
J. Karvonen
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Estimation Algorithm ◽  
Sea Ice Concentration ◽  
Finnish Meteorological Institute ◽  
Brightness Temperatures ◽  
Concentration Estimation ◽  
Ice Concentration ◽  
Bootstrap Algorithm ◽  
The University

Abstract. We have studied the possibility of combining the high-resolution synthetic aperture radar (SAR) segmentation and ice concentration estimated by radiometer brightness temperatures. Here we present an algorithm for mapping a radiometer-based concentration value for each SAR segment. The concentrations are estimated by a multi-layer perceptron (MLP) neural network which has the AMSR-2 (Advanced Microwave Scanning Radiometer 2) polarization ratios and gradient ratios of four radiometer channels as its inputs. The results have been compared numerically to the gridded Finnish Meteorological Institute (FMI) ice chart concentrations and high-resolution AMSR-2 ASI (ARTIST Sea Ice) algorithm concentrations provided by the University of Hamburg and also visually to the AMSR-2 bootstrap algorithm concentrations, which are given in much coarser resolution. The differences when compared to FMI daily ice charts were on average small. When compared to ASI ice concentrations, the differences were a bit larger, but still small on average. According to our comparisons, the largest differences typically occur near the ice edge and sea–land boundary. The main advantage of combining radiometer-based ice concentration estimation and SAR segmentation seems to be a more precise estimation of the boundaries of different ice concentration zones.

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