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遥感技术与应用  2022, Vol. 37 Issue (5): 1109-1118    DOI: 10.11873/j.issn.1004-0323.2022.5.1109
LiDAR专栏     
激光雷达数据辅助的FY-3D影像阈值自适应云检测方法
张宇卓(),李志伟,沈焕锋(),彭小元
武汉大学 资源与环境科学学院,湖北 武汉 430079
Threshold Adaptive Cloud Detection for FY-3D Images Using CALIPSO Data as Reference
Yuzhuo Zhang(),Zhiwei Li,Huanfeng Shen(),Xiaoyuan Peng
School of Resource and Environmental Sciences,Wuhan University,Wuhan 430079,China
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摘要:

国产风云系列卫星可为全球范围内大气、陆地和海洋的遥感监测提供重要数据支撑,由于光学卫星影像不可避免受到云覆盖的影响,通过云检测获取准确的云掩膜是风云系列卫星影像精细处理与应用的关键。现有的云检测方法大多采用简单高效的阈值法,然而由于传感器光谱响应以及不同场景云覆盖下垫面的辐射差异,在缺少大量真实云覆盖标记情况下,现有方法往往难以确定最优的检测阈值。鉴于此,提出了一种阈值自适应的云检测方法(TACD),顾及传感器波段特性以及云覆盖下垫面差异,设置不同场景下的多通道阈值测试,包括反射率及反射率组合测试、亮度温度测试、亮度温度差异值测试、卷云测试等,联合具有高精度云层信息的激光雷达数据构建全球范围的云检测样本集,实现基于样本集真实云标记的迭代阈值优化,最终基于最优的阈值进行云检测。以风云三号(FY-3D)MERSI-II影像为例,联合CALIOP云层数据构建全球范围的云检测数据集,并将所提出的TACD方法云检测结果与官方云掩膜产品进行对比,结果表明该方法较官方云检测算法精度有明显提高,其中平均交并比从80.35%提升至84.09%,召回率可达92.67%,具有业务化应用的潜力。

关键词: 云检测阈值自适应风云三号CALIPSOTACD    
Abstract:

FY series satellites can provide important data support for remote sensing monitoring of the atmosphere, land, and ocean on a global scale. As optical satellite images are inevitably affected by cloud coverage, obtaining accurate cloud masks through cloud detection is the key to the processing and application of FY series satellite images. Most of the existing cloud detection methods use simple and efficient threshold methods, however, the optimal threshold in the traditional threshold method is difficult to determine in the absence of a large number of cloud and clear sky labels due to differences in sensor spectral response and radiance differences between different underlying surfaces. Therefore, a Threshold Adapted Cloud Detection (TACD) method is proposed in this paper, which has taken the band characteristics and underlying surfaces differences into consideration comprehensively, then sets up multi-channel threshold tests consisting of reflectance and reflectance combination test, brightness temperature test, brightness temperature difference test and cirrus cloud test under different scenarios, and establish global Optical-LiDAR cloud detection dataset to achieve iteratively optimize thresholds in TACD algorithm, and finally perform cloud detection based on the optimal thresholds. We take FY-3D MERSI-II images as an example to establish a high-precision global cloud detection sample dataset collocated with CALIOP cloud layer data, compare the cloud detection results of the proposed TACD method with the official cloud mask products. The evaluation results show that the accuracy of the cloud masks produced by TACD is significantly improved compared with the official masks, in which the mIoU is increased from 80.35% to 84.09% and the recall can reach 92.67%. In conclusion, TACD has great potential for application.

Key words: Cloud detection    Threshold adaptive method    FY-3D    CALIPSO    TACD
收稿日期: 2021-12-28 出版日期: 2022-12-13
ZTFLH:  TP75  
基金资助: 国家自然科学基金项目(41971303);中国博士后科学基金项目(2021M692462)
通讯作者: 沈焕锋     E-mail: yuzhuozhang816@whu.edu.cn;shenhf@whu.edu.cn
作者简介: 张宇卓(1995-),女,河北石家庄人,硕士研究生,主要从事遥感图像处理方面的研究。E?mail: yuzhuozhang816@whu.edu.cn
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引用本文:

张宇卓,李志伟,沈焕锋,彭小元. 激光雷达数据辅助的FY-3D影像阈值自适应云检测方法[J]. 遥感技术与应用, 2022, 37(5): 1109-1118.

Yuzhuo Zhang,Zhiwei Li,Huanfeng Shen,Xiaoyuan Peng. Threshold Adaptive Cloud Detection for FY-3D Images Using CALIPSO Data as Reference. Remote Sensing Technology and Application, 2022, 37(5): 1109-1118.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2022.5.1109        http://www.rsta.ac.cn/CN/Y2022/V37/I5/1109

图1  多通道阈值自适应云检测算法流程图
图2  CALIPSO数据与FY-3D MERSI-II影像空间匹配
图3  多通道阈值测试
海洋场景陆地场景
HOT>0.11>0.11
VBR>0.45>0.40
NDSIN/A>-0.3 & <0.59
Rred>0.06>0.06
R1.38μm>0.001N/A
R1.03μm>0.05N/A
BT11<290 KN/A
BT7.2-BT11>-29 KN/A
BT3.8-BT11>6.5 KN/A
BT8.6-BT11>-1 KN/A
表1  阈值优化所确定的最优阈值
图4  云检测结果示例
总体精度召回率准确率平均交并比F1分数
FY-3D CLM184.9191.3189.2882.2990.28
FY-3D CLM283.6287.2491.0580.3589.10
TACD算法86.5492.6790.0884.0991.35
TACD(海洋)86.5392.6490.1184.0991.36
TACD(陆地)87.2895.5686.6983.3390.91
表2  结果精度验证 (%)
图5  多场景云检测结果示例
图6  基于引导滤波的云掩膜后处理示例
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