Detection of Arctic Sea Ice Using 89 GHz Microwave Radiometer Channels

Yue Zhao; Xingdong Wang; Changfeng Luo

doi:10.62762/TIOT.2024.528361

Article Information

Published in ICCK Transactions on Internet of Things

Volume/Issue Volume 2, Issue 2, 2024

Pages 36-43

Abstract

Sea ice is a crucial component of the cryosphere, and extensive research has been conducted on sea ice using microwave remote sensing due to its robustness against cloud cover and illumination variations. This paper focuses on classifying Arctic sea ice based on microwave remote sensing data. Leveraging the high stability of microwave radiometers, we analyze the characteristics of different sea ice types across the Arctic region in January 2017 using high-resolution AMSR-E/AMSR2 data at the 89 GHz frequency band. Data at this frequency are less susceptible to cloud and water vapor interference, while lower frequency bands have traditionally been more commonly used in similar studies. However, our study emphasizes the significance of the 89 GHz frequency band, which offers high-resolution data for distinguishing between multi-year ice, first-year ice, and open water. The brightness temperature differences among these sea ice types are analyzed, and a method based on these differences is proposed for classification. The fine tree algorithm in MATLAB’s decision tree toolbox is employed to generate the classification results.

Graphical Abstract

Detection of Arctic Sea Ice Using 89 GHz Microwave Radiometer Channels

Keywords

Sea ice classification Arctic Microwave remote sensing Decision tree

Funding

This work was supported without any funding.

References

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Cite This Article

APA Style

Zhao, Y., Wang, X., & Luo, C. (2024). Arctic Sea Ice Detection based on Microwave Radiometer in 89 GHz Channels. ICCK Transactions on Internet of Things, 1(1), 36–43 https://doi.org/10.62762/TIOT.2024.528361

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TY  - JOUR
AU  - Zhao, Yue
AU  - Wang, Xingdong
AU  - Luo, Changfeng
PY  - 2024
DA  - 2024/04/07
TI  - Detection of Arctic Sea Ice Using 89 GHz Microwave Radiometer Channels
JO  - ICCK Transactions on Internet of Things
T2  - ICCK Transactions on Internet of Things
JF  - ICCK Transactions on Internet of Things
VL  - 2
IS  - 2
SP  - 36
EP  - 43
DO  - 10.62762/TIOT.2024.528361
UR  - https://www.icck.org/article/abs/TIOT.2024.528361
KW  - Sea ice classification
KW  - Arctic
KW  - Microwave remote sensing
KW  - Decision tree
AB  - Sea ice is a crucial component of the cryosphere, and extensive research has been conducted on sea ice using microwave remote sensing due to its robustness against cloud cover and illumination variations. This paper focuses on classifying Arctic sea ice based on microwave remote sensing data. Leveraging the high stability of microwave radiometers, we analyze the characteristics of different sea ice types across the Arctic region in January 2017 using high-resolution AMSR-E/AMSR2 data at the 89 GHz frequency band. Data at this frequency are less susceptible to cloud and water vapor interference, while lower frequency bands have traditionally been more commonly used in similar studies. However, our study emphasizes the significance of the 89 GHz frequency band, which offers high-resolution data for distinguishing between multi-year ice, first-year ice, and open water. The brightness temperature differences among these sea ice types are analyzed, and a method based on these differences is proposed for classification. The fine tree algorithm in MATLAB’s decision tree toolbox is employed to generate the classification results.
SN  - pending
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  -

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@article{Zhao2024Detection,
  author = {Yue Zhao and Xingdong Wang and Changfeng Luo},
  title = {Detection of Arctic Sea Ice Using 89 GHz Microwave Radiometer Channels},
  journal = {ICCK Transactions on Internet of Things},
  year = {2024},
  volume = {2},
  number = {2},
  pages = {36-43},
  doi = {10.62762/TIOT.2024.528361},
  url = {https://www.icck.org/article/abs/TIOT.2024.528361},
  abstract = {Sea ice is a crucial component of the cryosphere, and extensive research has been conducted on sea ice using microwave remote sensing due to its robustness against cloud cover and illumination variations. This paper focuses on classifying Arctic sea ice based on microwave remote sensing data. Leveraging the high stability of microwave radiometers, we analyze the characteristics of different sea ice types across the Arctic region in January 2017 using high-resolution AMSR-E/AMSR2 data at the 89 GHz frequency band. Data at this frequency are less susceptible to cloud and water vapor interference, while lower frequency bands have traditionally been more commonly used in similar studies. However, our study emphasizes the significance of the 89 GHz frequency band, which offers high-resolution data for distinguishing between multi-year ice, first-year ice, and open water. The brightness temperature differences among these sea ice types are analyzed, and a method based on these differences is proposed for classification. The fine tree algorithm in MATLAB’s decision tree toolbox is employed to generate the classification results.},
  keywords = {Sea ice classification, Arctic, Microwave remote sensing, Decision tree},
  issn = {pending},
  publisher = {Institute of Central Computation and Knowledge}
}

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