Sea Ice Detection by an Unsupervised Method Using Ku- and Ka-Band Radar Data at Low Incidence Angles: First Results

This paper presents the first results of sea ice detection using the data of Ka- and Ku-band radars at low incidence angles. A classification method based on an unsupervised K-means approach is applied to the arrays of the data for the Arctic and Antarctic regions. Comparison with Advanced Microwave...

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Bibliographic Details
Published in:Remote Sensing
Main Authors: Maria Panfilova, Vladimir Karaev
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2023
Subjects:
dual frequency precipitation radar
global precipitation measurement satellite
near nadir normalized radar cross section
sea ice detection
clustering
Science
Q
Antarctic
Arctic
Antarc*
Sea ice
Online Access:https://doi.org/10.3390/rs15143530
https://doaj.org/article/5e9cb6015c3b40149388436cbb8b659c
Description
Summary:This paper presents the first results of sea ice detection using the data of Ka- and Ku-band radars at low incidence angles. A classification method based on an unsupervised K-means approach is applied to the arrays of the data for the Arctic and Antarctic regions. Comparison with Advanced Microwave Scanning Radiometer 2 (AMSR-2) data was performed, and the dependence of classification performance was evaluated for incidence angles from 0° to 18.15°. This paper evaluates the classification accuracy of sea ice detection based on Ku-band, Ka-band, and their combination. Preliminary results indicate that the classification based solely on Ku-band data achieves the best performance.

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