首页|期刊导航|大气和海洋科学快报（英文版）|Deep learning in extracting tropical cyclone intensity and wind radius information from satellite infrared images—A review
大气和海洋科学快报（英文版）2023，Vol.16Issue(4)：65-71,7.DOI:10.1016/j.aosl.2023.100373
Deep learning in extracting tropical cyclone intensity and wind radius information from satellite infrared images—A review
Deep learning in extracting tropical cyclone intensity and wind radius information from satellite infrared images—A review
摘要
Abstract
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.关键词
热带气旋/深度学习/遥感/信息提取Key words
Tropical cyclone/Deep learning/Remote sensing/Information extraction引用本文复制引用
Chong Wang,Xiaofeng Li..Deep learning in extracting tropical cyclone intensity and wind radius information from satellite infrared images—A review[J].大气和海洋科学快报（英文版）,2023,16(4):65-71,7.基金项目
This work was supported the Strategic Priority Research Program of the Chinese Academy of Sciences[grant number XDB42000000],the National Natural Science Foundation of China[grant number U2006211],the Major Scientific and Technological Innovation Projects in Shandong Province[grant number 2019JZZY010102],and the Chi-nese Academy of Sciences program[grant number Y9KY04101L]. （）
