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基于FY-3/MERSI卫星资料的霾判识方法研究
引用本文:陈英英,熊守权,周毓荃,舒斯,何明琼.基于FY-3/MERSI卫星资料的霾判识方法研究[J].气象,2017,43(11):1431-1438.
作者姓名:陈英英  熊守权  周毓荃  舒斯  何明琼
作者单位:湖北省气象服务中心,武汉 430205,湖北省气象服务中心,武汉 430205,中国气象科学研究院,北京 100081,湖北省气象服务中心,武汉 430205,湖北省气象服务中心,武汉 430205
基金项目:国家重点研发计划(2016YFA0601700)和风云三号(02)批气象卫星地面应用系统工程应用示范系统项目(FY-3(02)-UDS-1.4.1)共同资助
摘    要:选取2015年12月25日及2016年1月18日两次覆盖湖北的重污染天气过程,利用FY-3A(B)/MERSI卫星资料和气象、环境监测资料,应用图像色彩处理技术、可见光近红外通道反射率分析等技术,开展对湖北地区霾的遥感识别研究。研究结果表明:以不同波段进行红绿蓝三通道合成时,霾可以被识别,其中以全可见光模式合成时,霾以灰白色为主,比周围的云雾区略暗;以可见光、近红外、红外三通道合成时,霾以紫色、紫灰色为主,云类识别精细;以可见光、近红外两通道增强显示合成时,霾以紫灰色为主,与晴空地表及云区差异明显,但易将由小粒子组成的薄卷云误判为霾,需通过云顶黑体亮温进行剔除。通过建立红外亮温和可见光反射率识别指标,可将霾与晴空、厚云区区分开来,但很难与低云/雾区进行有效区分,加入对有效粒子半径敏感的近红外通道反射率后,借助两者在粒子大小上的差异,可在一定程度上解决这一问题,并通过地面人工观测资料进行分析验证。

关 键 词:风云三号卫星,霾,卫星资料,彩色云图,反射率,识别
收稿时间:2016/5/21 0:00:00
修稿时间:2017/9/11 0:00:00

Study on Identification Index of Haze Spectrum by FY-3/MERSI Satellite Data
CHEN Yingying,XIONG Shouquan,ZHOU Yuquan,SHU Si and HE Mingqiong.Study on Identification Index of Haze Spectrum by FY-3/MERSI Satellite Data[J].Meteorological Monthly,2017,43(11):1431-1438.
Authors:CHEN Yingying  XIONG Shouquan  ZHOU Yuquan  SHU Si and HE Mingqiong
Institution:Hubei Meteorological Service Centre, Wuhan 430205,Hubei Meteorological Service Centre, Wuhan 430205,Chinese Academy of Meteorological Sciences, Beijing 100081,Hubei Meteorological Service Centre, Wuhan 430205 and Hubei Meteorological Service Centre, Wuhan 430205
Abstract:Selecting two heavy pollution weather processes cover Hubei on 25 December 2015 and 18 January 2016, and using FY 3A (B)/MERSI satellite data and weather observation, environmental monitoring data, this paper carries out the study of haze remote sensing identification by digitizing the image color processing technology and technology of reflectance threshold of visible and near infrared channels in Hubei area. The results show that haze can be distinguished by the color composition of red, green and blue channels. With full visible bands, the color of haze is mainly gray white, slightly darker than the surrounding cloud area; with visible, infrared and near infrared bands, the color of haze is mainly purple and purple grey, and the cloud class recognition is more fine; and with enhanced display of visible and near infrared bands, the color of haze is mainly purple grey, which can be distinguished from the clear sky surface and cloud area, but easy to be confused with the thin cirrus composed of small particles, so it needs to be eliminated through the blackbody brightness temperature. With the help of TBB of infrared channel and the visible reflectance index, haze can be identified from the clear sky and thick cloud area, but difficult to distinguish from mist. The problem can be solved by adding the reflectance of near infrared channel which is sensitive to the effective particle radius. Finally the results are verified through the observation of ground weather phenomena.
Keywords:FY-3 satellite  haze  satellite data  color cloud image  reflectance  identification
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