Deep learning in extracting tropical cyclone intensity and wind radius information from satellite infrared images——A review

被引：0
|
作者：
Chong Wang [1 ,2 ]
Xiaofeng Li [1 ]
机构：
[1] Key Laboratory of Ocean Circulation and Waves,Institute of Oceanology
[2] University of Chinese Academy of Sciences
来源：
Atmospheric and Oceanic Science Letters | 2023年 / 16卷 / 04期
基金：
中国国家自然科学基金;
关键词：
热带气旋; 深度学习; 遥感; 信息提取;
D O I：
暂无
中图分类号：
P407 [大气遥感];
学科分类号：
1404 ;
摘要：
热带气旋(TC)严重危害人类生命和财产安全,TC的实时监测一直是研究热点,随着空间和传感器技术的发展,卫星遥感已成为监测TC的主要手段.此外,深度学习具有卓越的数据挖掘能力,在地球科学中的表现优于基于物理或统计的算法,越来越多的深度学习算法被开发和应用于TC信息的提取,本文系统地回顾了深度学习在TC信息提取中的应用,并给出了深度学习模型在TC强度和风圈半径提取中的应用.此外,本文还展望了深度学习在TC信息提取中的应用前景.
引用
收藏
页码：67 / 73
页数：7
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