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遥感技术与应用  2020, Vol. 35 Issue (1): 141-152    DOI: 10.11873/j.issn.1004-0323.2020.1.0141
模型与反演     
太湖水体GF-1/WFV影像的6S逐像元大气校正
程春梅1(),韦玉春2(),李渊3,涂乾光1
1. 浙江水利水电学院 测绘与市政工程学院,浙江 杭州 310018
2. 南京师范大学虚拟地理环境教育部重点实验室,江苏 南京 210023
3. 浙江工商大学 旅游与城乡规划学院,浙江 杭州 310018
Atmospheric Correction of GF-1/WFV Image in Taihu Lake based on the 6S Model Pixel by Pixel
Chunmei Cheng1(),Yuchun Wei2(),Yuan Li3,Qianguang Tu1
1. College of Geomatics and Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
2. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
3. School of Tourism and Urban-rural Planning, Zhejiang Gongshang University, Hangzhou 310018, China
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摘要:

水体光谱信息微弱,常用的基于辐射传输模型的大气校正方法在水体中校正精度较差。基于覆盖太湖水体的2016年4月29日的高分一号宽幅相机影像(GF-1/WFV)和同步的实测光谱数据,对6S辐射传输模型的输入参数进行敏感性分析,逐像元计算观测几何,使用分区气溶胶类型、分区暗像元和Spline插值确定的气溶胶光学厚度(Aerosol Optical Depth,AOD)进行6S逐像元大气校正。实验结果表明:气溶胶模式对6S大气校正结果的影响最大,与FLAASH方法相比,逐像元计算观测几何和气溶胶参数的校正方法对大气校正精度有改进作用,4个波段的平均相对误差分别降低了1.84%、7.78%、4.79%和17%。结合精确大气参数输入的6S逐像元大气校正方法可以改进水体表面遥感反射率的大气校正精度。

关键词: 高分一号WFV大气校正6S太湖    
Abstract:

The spectral information of water is weak, and the commonly used radiation transfer model has poor accuracy in atmospheric correction of water body. Based on the Gaofen-1 WFV image (GF-1/WFV) and the synchronous in situ spectra covering Taihu Lake on 29th, April, 2016, the sensitivity analysis of the input parameters in 6S model was first performed, and then the image was corrected using 6S model using the observation geometry calculated pixel-by-pixel, the partitioned aerosol type and the Aerosol Optical Depth (AOD) determined by the partitioned dark pixel and Spline interpolation. The experimental results show that the aerosol type has the greatest influence on the 6S atmospheric correction results. Compared with the FLAASH method, the 6S method using the observation geometry and aerosol parameters calculated pixel-by-pixel significantly improved the atmospheric correction accuracy, with the ARE (Average Relative Error) of the four bands reduced by 1.84%,7.78%,4.79%,17%. The 6S atmospheric correction method pixel by pixel with the input of accurate atmospheric parameters can improve the correction accuracy of the remote sensing reflectance above water surface.

Key words: GF-1    WFV    Atmospheric correction    6S    Taihu Lake
收稿日期: 2018-10-07 出版日期: 2020-04-01
ZTFLH:  TP79  
基金资助: 国家自然科学基金项目“面向二类水体叶绿素a浓度遥感反演的光谱纯化研究”(41471283);浙江省自然科学青年基金项目“基于多源卫星遥感的中国近海海洋锋面日变化研究”(LQ18D060002);浙江省水利厅科技项目“基于遥感蒸散发的灌溉水有效利用系数测算研究”(RC1814)
通讯作者: 韦玉春     E-mail: ccm8711@163.com;weiyuchun@njnu.edu.cn
作者简介: 程春梅(1987-),女,湖北武汉人,博士,讲师,主要从事水环境遥感研究。E?mail:ccm8711@163.com
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引用本文:

程春梅,韦玉春,李渊,涂乾光. 太湖水体GF-1/WFV影像的6S逐像元大气校正[J]. 遥感技术与应用, 2020, 35(1): 141-152.

Chunmei Cheng,Yuchun Wei,Yuan Li,Qianguang Tu. Atmospheric Correction of GF-1/WFV Image in Taihu Lake based on the 6S Model Pixel by Pixel. Remote Sensing Technology and Application, 2020, 35(1): 141-152.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.1.0141        http://www.rsta.ac.cn/CN/Y2020/V35/I1/141

图1  太湖采样点位置图
图2  实测遥感反射率和拟合后WFV波段反射率
图3  3个样点不同气溶胶模式校正后的遥感反射率
图4  3个样点不同AOD校正后的遥感反射率
原始影像 裁剪后影像
ID 太阳天顶角/° 太阳方位角/° 卫星天顶角/° 太阳天顶角/° 太阳方位角/° 卫星天顶角/°
1 19.33 152.61 17.89 18.71 155.70 9.10
2 18.50 159.87 0.26 18.45 158.06 6.46
3 17.30 149.58 17.89 18.11 154.67 8.95
4 16.37 157.36 0.26 17.87 157.39 8.14
表1  原始影像和裁剪后影像4个角点的观测几何
图5  基于分区暗像元和Spline 插值的太湖AOD分布
图6  逐像元6S大气校正流程图
图7  大气校正前后遥感影像和遥感反射率
图8  6S和FLAASH大气校正结果与实测光谱对比
6S逐像元 FLAASH模型
ARE/% RMSE ARE/% RMSE
波段1 13.65 0.007 2 15.49 0.008 5
波段2 13.8 0.008 5 21.58 0.011 0
波段3 16.35 0.006 8 21.14 0.008 4
波段4 108.3 0.014 9 125.3 0.017 0
平均值 38.02 0.009 4 45.87 0.011 2
表2  6S和FLAASH大气校正方法的平均相对误差和均方根误差
图9  6S 逐像元大气校正与FLAASH校正平均相对误差
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