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    Volume 2, Issue 1, IECE Transactions on Internet of Things
    Volume 2, Issue 1, 2024
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    Jinchao Chen
    Jinchao Chen
    School of Computer Science, Northwestern Polytechnical University, Xi’an 710129, China
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    IECE Transactions on Internet of Things, 2024, Volume 2, Issue 1: 26-35

    Free Access | Research Article | 12 March 2024
    Advancements in Multi-Year Ice Concentration Estimation from SSM/I 91.6GHz Observations
    by
    IECE Author Yue Zhao 1 *
    IECE Author Xingdong Wang 1
    IECE Author Zifan Zhang 1
    1 College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China
    * Corresponding author: Yue Zhao, email: ZhaoY91028@hotmail.com
    DOI: 10.62762/TIOT.2024.682080
    Received: 15 January 2024, Accepted: 27 February 2024, Published: 12 March 2024  
    Abstract
    To enhance the LOMAX algorithm for sea ice concentration analysis in the polar regions, SSM/I 91.6GHz data was utilized, addressing the underuse of higher frequency data. The refinement process involved redefining PCT values for one-year and multi-year ice regions through both interpolation and least squares methods. Moreover, band operations were conducted to facilitate Arctic multi-year ice concentration retrieval. Comparative analyses with the NT algorithm indicated that the Arctic sea ice extents determined by both algorithms were similar, affirming the credibility of the modified LOMAX algorithm. When examining the results for March and September, the updated LOMAX algorithm demonstrated improved accuracy over the NT algorithm, especially under summer ice melt conditions, highlighting the enhanced performance and reliability of the refined algorithm in various seasonal contexts.
    Graphical Abstract
    Advancements in Multi-Year Ice Concentration Estimation from SSM/I 91.6GHz Observations
    Keywords
    LOMAX
    Multi-year ice concentration
    91.6 GHz
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    Cite This Article
    APA Style
    Zhao, Y., Wang, X., & Zhang, Z. (2024). Advancements in Multi-Year Ice Concentration Estimation from SSM/I 91.6GHz Observations. IECE Transactions on Internet of Things, 2(1), 26–35. https://doi.org/10.62762/TIOT.2024.682080
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