一种基于FY3D/MERSI2的AOD遥感反演方法

doi:10.12082/dqxxkx.2020.190206

摘要/Abstract

摘要：

针对目前国产卫星对气溶胶遥感监测应用较少的情况,本研究综合暗象元和SARA算法优势,基于FY-3D MERSI2数据构建了一套气溶胶光学厚度(Aerial Optical Depth, AOD)快速遥感反演方法。首先,引入了传统暗象元算法中的地表反射率经验关系,然后利用AERONET长时间序列的地基观测数据,构建了红波段和蓝波段气溶胶光学厚度、不对称因子和单次散射率之间的关系,最后利用MOD04和AERONET的AOD产品对研究反演结果进行了验证和评估分析。结果发现：① 本研究反演的AOD不仅保持了与MODIS的气溶胶产品空间分布的一致性,而且合理地呈现了AOD的高值分布,改进了MOD04气溶胶产品在云和亮目标方面反演缺失问题;② 利用AERONET地基观测结果对本研究获取的MERSI2的AOD反演结果进行了对比分析,发现二者具有较高的线性相关性,蓝波段AOD线性相关系数超过0.85;③ 利用MERSI2数据完整地捕捉到了2018年3月9—14日京津冀及周边区域的一次重污染过程中气溶胶时空分布变化情况,这也说明了FY3D卫星具备良好的气溶胶遥感监测能力,为我国灰霾监测和预警提供参考依据。本研究对大力发展国产卫星在大气环境遥感的应用有重要参考意义。

关键词: 高分辨率遥感FY3D/MERSI, 气溶胶光学厚度, 简化的气溶胶遥感反演算法, 暗象元, 遥感反演, AERONET, 地表反射率, 对比验证

Abstract:

Until now, relatively few researches of aerosols retrieval have been conducted using domestic satellite remote sensing. To promote domestic satellite remote sensing applications, a set of rapid inversion technology of Aerosol Optical Depth (AOD) using remote sensing was developed in this study based on FY-3D/MERSI2 data, which combined the advantages of Dark Target (DT) and SARA algorithm. Firstly, the empirical relationship of surface reflectance in traditional Dark Target algorithm was introduced to get the red and blue band surface reflectance. Then, the relationships between aerosol optical thickness, asymmetry factor, and single scattering albedo in red and blue bands were established using long time-series ground observation data from AERONET. Finally, MOD04 and AERONET AOD products were used to validate and evaluate the inversion results. Results show that the AOD retrieved from MERSI2 in this study not only kept the spatial consistency with the MODIS aerosol product, but also presented a reasonable distribution of high AOD values, which improved the AOD inversion in cloud and bright target areas where values were missing in MOD04 aerosol product. Meanwhile, compared with ground-based observations, the proposed algorithm also demonstrated a higher accuracy with an average correlation coefficient greater than 0.85 at the 470nm band. These two methods showed a strong linear correlation at blue band. Finally, the spatial and temporal distribution of aerosols during a heavy pollution in Beijing, Tianjin, Hebei, and surrounding areas from March 9 to March 14 in 2018 was completely captured using MERSI2, which indicated that FY3D satellite was able to monitor aerosols and could provide a reference for haze monitoring and early warning in China. This study provides important reference significance for the development and application of domestic satellites in atmospheric remote sensing business.

Key words: high-resolution remote sensing FY3D/MERSI, aerosol optical depth, Simplified Aerosol Retrieval Algorithm, Dark Target (DT), remote sensing inversion, AERONET, surface reflectance, comparison validation

陈辉, 厉青, 王中挺, 马鹏飞, 李营, 赵爱梅. 一种基于FY3D/MERSI2的AOD遥感反演方法[J]. 地球信息科学学报, 2020, 22(9): 1887-1896.DOI:10.12082/dqxxkx.2020.190206

CHEN Hui, LI Qing, WANG Zhongting, MA Pengfei, LI Ying, ZHAO Aimei. Retrieval of Aerosol Optical Depth Using FY3D MERSI2 Data[J]. Journal of Geo-information Science, 2020, 22(9): 1887-1896.DOI:10.12082/dqxxkx.2020.190206

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波段序号	中心波长/nm	光谱带宽/nm	空间分辨率/m	主要用途
1	470	50	250	获取蓝波段大气辐射传输方程,云像元识别
3	650	50	250	获取红波段大气辐射传输方程
7	2130	50	1000	根据经验公式计算红、蓝波段地表反射率,水体和暗像元识别
25	12 000	1000	250	云像元识别