双向反射分布函数
遥感
气溶胶
离散余弦变换
中分辨率成像光谱仪
卫星
算法
航空网
计算机科学
环境科学
气象学
反射率
人工智能
地质学
图像(数学)
地理
物理
光学
天文
作者
Xinpeng Tian,Qiang Liu,Zhiqiang Gao,Yueqi Wang,Xiuhong Li,Jing Wei
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing
[Institute of Electrical and Electronics Engineers]
日期:2021-12-01
卷期号:59 (12): 9851-9860
被引量:6
标识
DOI:10.1109/tgrs.2020.3048109
摘要
The retrieval of aerosol properties over land from satellite sensors has always been a challenge. At present, several different algorithms for retrieving aerosol optical depth (AOD) have been developed from different satellite sensors. While each algorithm has its own advantages, the accuracy of AOD retrieval still needs to be further improved. To improve the retrieval accuracy of aerosol algorithms, it is necessary to provide a better method to describe the surface properties. In the current study, a new aerosol retrieval algorithm for Moderate Resolution Imaging Spectroradiometer (MODIS) images at a high spatial resolution of 500 m is proposed based on $a$ priori bidirectional reflectance distribution function (BRDF) shape parameters database, which is reconstructed via the 3-D discrete cosine transform (DCT-PLS) method. Then, the surface reflectances are calculated from BRDF model (i.e., RossThick-LiSparse), and a non-Lambertian forward model used to describe the surface anisotropy. The new algorithm is used for processing the MODIS over the Beijing–Tianjin–Hebei of China, and Southeastern United States of America regions, and results are validated against AERONET AOD measurements as well as compared with the MODIS AOD products. The comparison showed that the estimation scheme of surface reflectance in this new algorithm significantly improved the AOD retrievals accuracy, with average correlation coefficient ~0.965 and root-mean-square error ~0.125; the number of AOD retrievals falling within expected error has increased to ~80.1%, and the overestimation uncertainty has been reduced compared with MODIS products. Due to the high spatial resolution and continuous spatial distributions of the AOD retrievals by the new algorithm, therefore, it can well-captured aerosol details over mixed surfaces and better useful for air pollution studies than the MODIS products at local and urban scales.
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