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遥感技术与应用  2020, Vol. 35 Issue (2): 389-398    DOI: 10.11873/j.issn.1004-0323.2020.2.0389
数据与图像处理     
基于FY-4A数据的青藏高原多时相云检测方法
张永宏1,2(),杨晨阳2(),陶润喆2,王剑庚3,田伟4
1.南京信息工程大学 气象灾害预报预警与评估协同创新中心,江苏 南京 210044
2.南京信息工程大学 自动化学院,江苏 南京 210044
3.南京信息工程大学 大气物理学院,江苏 南京 210044
4.南京信息工程大学 计算机与软件学院,江苏 南京 210044
Multi-temporal Cloud Detection Method for Qinghai-Tibet Plateau based with FY-4A Data
Yonghong Zhang1,2(),Chenyang Yang2(),Runzhe Tao2,Jiangeng Wang3,Wei Tian4
1.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information & Technology, Nanjing 210044, China
2.School of Automation, Nanjing University of Information & Technology, Nanjing 210044, China
3.School of Atmospheric Physics, Nanjing University of Information & Technology, Nanjing 210044, China
4.School of computer science & Technology, Nanjing University of Information & Technology, Nanjing 210044, China
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摘要:

基于我国新一代静止气象卫星FY-4A/AGRI的4 km分辨率全圆盘数据,利用其高时间分辨率、高光谱分辨率的特点,提出一种青藏高原地区多时相多通道阈值组合的云检测方法,并通过实际案例分析所提出的云检测方法有效可行。结果表明:对比中国国家气象中心云检测产品以及传统单时相云检测方法,多时相云检测方法,其准确率为94.4%,误检率为7.2%,漏检率为5.6%,均优于其他两种方法,体现了多时相检测的优越性;云相态检测中,分别使用GPM降水资料以及CALIPSO卫星云相态观测结果对检测结果进行精度评价,其中冰云分布与GPM实测降水分布相似度达到了0.883,云相态整体检测结果与CALIPSO实际观测的云相态也较吻合,进一步验证了云相态检测的合理性,这也是对青藏高原地区进行降水监测的一种辅助手段。

关键词: 青藏高原地区云检测FY?4A多时相GPMCALIPSO    
Abstract:

Based on the 4 km resolution full-disc data of China's new generation of geostationary meteorological satellite FY-4A/AGRI, using its high temporal resolution and high spectral resolution, a multi-temporal multi-channel threshold combination cloud detection in the Qinghai-Tibet Plateau is proposed. Compared with the China National Meteorological Center cloud detection products and the traditional single-phase cloud detection method, the multi-time phase cloud detection method has an accuracy rate of 94.4%, a false detection rate of 7.2%, and a missed detection rate of 5.6%; In the cloud phase detection, the GPM precipitation and the CALIPSO satellite cloud phase observation were used to evaluate the accuracy of the detection results. The similarity between cloud phase detection result and GPM data reaches 0.883. The result of the cloud phase and the actual CALIPSO observation is also close. The rationality of cloud phase detection is verified, and it is also an auxiliary means for precipitation monitoring in the Qinghai-Tibet Plateau.

Key words: Qinghai-Tibet Plateau    Cloud detection    FY-4A    Multi-temporal    GPM    CALIPSO
收稿日期: 2018-12-05 出版日期: 2020-07-10
ZTFLH:  P426.63+5  
基金资助: 国家自然科学基金项目“中尼公路沿线山地灾害遥感监测与预警研究”(41661144039)
通讯作者: 杨晨阳     E-mail: zyh@nuist.edu.cn;1137079132@qq.com
作者简介: 张永宏(1974-),男,山东临沂人,教授,主要从事大气遥感检测、图像处理分析研究。E?mail:zyh@nuist.edu.cn
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引用本文:

张永宏,杨晨阳,陶润喆,王剑庚,田伟. 基于FY-4A数据的青藏高原多时相云检测方法[J]. 遥感技术与应用, 2020, 35(2): 389-398.

Yonghong Zhang,Chenyang Yang,Runzhe Tao,Jiangeng Wang,Wei Tian. Multi-temporal Cloud Detection Method for Qinghai-Tibet Plateau based with FY-4A Data. Remote Sensing Technology and Application, 2020, 35(2): 389-398.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.2.0389        http://www.rsta.ac.cn/CN/Y2020/V35/I2/389

卫星通道波长/μm分辨率/km
10.461
20.640.5~1
30.861
41.382
51.612
62.252~4
73.82
83.84
96.54
107.24
118.54
1210.84
1312.04
1413.34
表1  FY-4A通道参数
图1  算法流程图
指标公式
I1R0.64>a
I2NDCI>b
I3NDSI>c
I4R0.45>d,R0.64>e
I5?BT<f
表2  算法判断指标
图2  云雪像元在不同波段数值变化曲线
指标R0.64 >aNDCI> bNDSI>cR0.46>d,&R0.64>eΔBT<f
阈值a=0.32b=0.15c=0.45d=0.15,e=0.25f=28
表3  云检测阈值
图3  各相态云像元在不同波段数值变化曲线
云相态冰云水云
识别条件NDSI > 0.65R1.61 < 0.35
BT10.8 < 225KBT10.8–BT12 > 6K
表4  云相态识别阈值
图4  本文算法检测结果与其他方法检测对比
图5  积雪提取结果
传统单时相法/%云产品/%本文算法/%
误检率12.822.57.2
漏检率22.39.75.6
准确率79.982.894.4
表5  算法精度对比情况
图6  云相态识别结果
图7  GPM降水数据
图8  云相态检测与CALIPSO卫星观测对比
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