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遥感技术与应用  2020, Vol. 35 Issue (2): 372-380    DOI: 10.11873/j.issn.1004-0323.2020.2.0372
模型与反演     
基于深蓝算法的Sentinel-2数据气溶胶光学厚度反演
徐玉雯1,2(),张浩2(),陈正超2,景海涛1
1.河南理工大学 测绘与国土信息工程学院, 河南 焦作 454000
2.中国科学院遥感与数字地球研究所 数字地球重点实验室, 北京 100094
Retrieval of AOD from Sentinel-2 Data based on Deep Blue Algorithm
Yuwen Xu1,2(),Hao Zhang2(),Zhengchao Chen2,Haitao Jing1
1.School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China
2.Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
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摘要:

中高分辨率气溶胶信息对于高精度地表反射率反演以及城市空气环境质量监测具有重大意义,但在城市及稀疏植被等高亮地表区域,气溶胶光学厚度(AOD)的高精度反演一直是定量遥感领域的难点之一。以北京城市区和包头沙漠区为例,利用MODIS地表反射率产品构建先验知识约束条件,基于深蓝算法实现了13景Sentinel-2高亮地表的AOD反演。为验证算法精度,将反演结果与全球气溶胶自动观测网(AERONET) 站点实测值、Sentinel-2官方插件Sen2Cor处理结果、Landsat-8反演值作对比。结果表明:①采用深蓝算法反演的AOD值与AERONET实测值具有显著的相关性(R2 >0.9,RMSE=0.056);②无论是沙漠高亮区还是植被较少的城市高亮区,Sen2Cor插件反演的AOD值整景均为固定值,无空间分布,不符合实际情况;③Sentinel-2深蓝算法反演结果与准同步过境的Landsat-8反演的AOD产品在空间分布上具有高度一致性,较好地反映了人类活动特征。相比于目前官方产品,深蓝算法适合Sentinel-2数据高亮区域的气溶胶反演,在绝对精度和空间分布趋势方面均具有明显优势。

关键词: 气溶胶光学厚度(AOD)深蓝算法(Deep Blue Algorithm)Sentinel?2A/B    
Abstract:

Medium-to-high resolution aerosol information is of great significance for surface reflectance inversion and urban ambient air quality monitoring. However, the high-precision aerosol optical thickness (AOD) retrieval in bright areas, such as cities and sparse vegetation areas, has long plagued the quantitative remote sensing applications. Taking Beijing urban area and Baotou desert area as examples, using MODIS surface reflectance products to construct prior knowledge constraints, the AOD inversion of 13 scenes Sentinel-2 images in bright areas was realized based on the deep blue algorithm. To verify the accuracy of the algorithm, the result were compared with the Sentinel-2 official algorithm processing result, the Landsat-8 official aerosol products and the ground-measured AOD data from the Global Aerosol Automated Observing Network (AERONET). The results indicate that the retrieved AOD values from deep blue algorithm is significantly correlated with the measured value of AERONET(R2 > 0.90, RMSE = 0.056 0), and the AOD spatial distributions are also well consistent with those from Landsat-8, which reflects the characteristics of human activities. But, whether in desert bright area or urban bright area with less vegetation, the AOD values retrieved by Sen2Cor plug-in are fixed, no spatial distribution and do not conform to the actual situation. In general, compared with the current official products, the deep blue algorithm is suitable for aerosol retrieval in high-brightness areas of Sentinel-2 data,and has obvious advantages in terms of estimation accuracy and spatial distribution trend.

Key words: Aerosol Optical Thickness(AOD)    Deep Blue Algorithm    Sentinel-2A/B
收稿日期: 2018-11-27 出版日期: 2020-07-10
ZTFLH:  TP79  
基金资助: 高分辨率对地观测系统重大专项“GF?6卫星数据大气校正技术”(30?Y20A02?9003?17/18);国家自然科学基金项目“中高分辨率多源光学遥感图像辐射归一化模型与方法研究”(41771397)
通讯作者: 张浩     E-mail: 1277300408@qq.com;zhanghao612@radi.ac.cn
作者简介: 徐玉雯(1994-),女,河南鹤壁人,硕士研究生,主要从事大气校正、辐射归一化方面的研究。E?mail: 1277300408@qq.com
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引用本文:

徐玉雯,张浩,陈正超,景海涛. 基于深蓝算法的Sentinel-2数据气溶胶光学厚度反演[J]. 遥感技术与应用, 2020, 35(2): 372-380.

Yuwen Xu,Hao Zhang,Zhengchao Chen,Haitao Jing. Retrieval of AOD from Sentinel-2 Data based on Deep Blue Algorithm. Remote Sensing Technology and Application, 2020, 35(2): 372-380.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2020.2.0372        http://www.rsta.ac.cn/CN/Y2020/V35/I2/372

图1  MODIS蓝波段与Sentinel-2A/B深蓝波段光谱响应函数图
类别光谱名称光谱库条数
coatingscoatings_beckman_440USGS7
coatings_beckman_449USGS3
coatings_beckman_3228USGS7
coatings_beckman_3516USGS3
manmademanmade_jhu_becknic_536ASTER20
mineralmineral_usgs_perknic_2756ASTER20
mixturesmixtures_beckman_3088USGS20
rockrock_usgs_perknic_2530ASTER20
soilsoil_jhu_becknic_2844ASTER20
vegetationvegetation_asd_2035USGS8
vegetation_beckman_438USGS12
volatilesvolatiles_asd_2151USGS18
volatiles_beckman_480USGS2
表1  选用的光谱种类和名称
图2  MODIS与Sentinel-2A/B蓝波段地表反射率的线性拟合图
图3  研究区RGB图像与AERONET地基站点空间分布(红色点)
图4  遥感反演AOD与AERONET AOD 散点对比图
北京城市区域包头沙漠区域
日期AOD值日期AOD值
2017-11-240.1122017-11-300.112
2017-12-190.1122017-12-100.165
2018-01-130.1422017-12-280.165
2018-02-120.1122018-03-250.201
2018-03-240.2012018-04-020.201
2018-04-080.2012018-05-040.201
2018-05-140.201
表2  Sentinel-2官方算法反演的AOD统计值
图5  2018年4月8日AOD反演结果
站点名称Beijing

Beijing_

PKU

Beijing_

RADI

Beijing_

CAMS

Xianghe
AERONET0.1910.1960.2040.1910.144
Landsat-80.1040.0920.1460.0930.100
深蓝算法0.2100.2410.2360.2030.189
表3  5个AERONET站点处AOD值比较
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