[1]高军,陈建,田晓宇.基于集成学习的风云四号遥感图像云相态分类算法[J].红外技术,2020,42(1):068-74.[doi:10.11846/j.issn.1001_8891.202001010]
 GAO Jun,CHEN Jian,TIAN Xiaoyu.Ensemble-learning-based Cloud Phase Classification Method for FengYun-4 Remote Sensing Images?[J].Infrared Technology,2020,42(1):068-74.[doi:10.11846/j.issn.1001_8891.202001010]
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基于集成学习的风云四号遥感图像云相态分类算法
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《红外技术》[ISSN:1001-8891/CN:CN 53-1053/TN]

卷:
42卷
期数:
2020年第1期
页码:
068-74
栏目:
出版日期:
2020-01-23

文章信息/Info

Title:
Ensemble-learning-based Cloud Phase Classification Method for FengYun-4 Remote Sensing Images?

文章编号:
1001-8891(2020)01-0068-07
作者:
高军12陈建1田晓宇1
1. 上海海事大学 信息工程学院;
2. 西藏自治区经济和信息化厅信息化推进处
Author(s):
GAO Jun12CHEN Jian1TIAN Xiaoyu1
1.College of Information Engineering, Shanghai Maritime University;
2. Information Promotion Office, Department of Economy and Information Technology of Tibet Autonomous Region

关键词:
云相态集成学习风云四号遥感图像处理
Keywords:
cloud phase ensemble learning FY-4 remote image processing
分类号:
TP389.1
DOI:
10.11846/j.issn.1001_8891.202001010
文献标志码:
A
摘要:
云相态分类在气象预报和气候研究中具有重要的地位。我国新一代气象卫星风云四号的成像仪在光谱通道数量和空间分辨率较上一代风云二号有较大提升,这为云相态的研究提供了新的遥感数据。本文首先对风云四号相隔15 min的遥感图像进行分析,然后提出亮温云相态指数,该指数可以进行初步云相态分类,最后在此基础上提出基于集成学习的云相态分类算法。实验结果与风云四号官方云相态分类结果进行比较,水云的一致率达到91.69%,冰云的一致率达到76.10%。
Abstract:
Cloud phase classification plays an important role in meteorological forecast and climate research. The image of meteorological satellite FengYun-4 (FY-4) has more channels and better resolution than FY-2. So it provides new remote sensing data for the study of the cloud phase. This study uses a brightness temperature cloud phase index to obtain cloud phase data. Thereafter, using the cloud phase data and ensemble learning algorithm, we develop a cloud phase classification model. By applying the cloud phase classification model, the predicted classification accuracy of water cloud and ice cloud are 91.69% and 76.10%, respectively.

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备注/Memo

备注/Memo:
收稿日期:2019-04-08;修订日期:2019-12-15.
作者简介:高军(1979-),男,浙江嘉兴人,博士,主要从事遥感信息处理、网络通信方面的研究。E-mail:jungao@shmtu.edu.cn。
基金项目:国家自然科学基金项目(61602296)。

更新日期/Last Update: 2020-01-20