Paper Info
Title
Satellite-Derived Aerosol Optical Depth Fusion Combining Active and Passive Remote Sensing Based on Bayesian Maximum Entropy
Abstract
Satellite-derived aerosol optical depth (AOD) is an important parameter for studies related to atmospheric environment, climate change, and biogeochemical cycle. Unfortunately, the relatively high data missing ratio of satellite-derived AOD limits the atmosphere-related research and applications to a certain extent. Accordingly, numerous AOD fusion algorithms have been proposed in recent years. However, most of these algorithms focused on merging AOD products from multiple passive sensors, which cannot complementarily recover the AOD missing values due to cloud obscuration and the misidentification between optically thin cloud and aerosols. In order to address these issues, a spatiotemporal AOD fusion framework combining active and passive remote sensing based on Bayesian maximum entropy methodology (AP-BME) is developed to provide satellite-derived AOD data sets with high spatial coverage and good accuracy in large scale. The results demonstrate that AP-BME fusion significantly improves the spatial coverage of AOD, from an averaged spatial completeness of 27.9%–92.8% in the study areas, in which the spatial coverage improves from 91.1% to 92.8% when introducing Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD data sets into the fusion process. Meanwhile, the accuracy of recovered AOD nearly maintains that of the original satellite AOD products, based on evaluation against ground-based Aerosol Robotic Network (AERONET) AOD. Moreover, the efficacy of the active sensor in AOD fusion is discussed through overall accuracy comparison and two case analyses, which shows that the provision of key aerosol information by the active sensor on haze condition or under thin cloud is important for not only restoring the real haze situations but also avoiding AOD overestimation caused by cloud optical depth (COD) contamination in AOD fusion results.
Year
DOI
Venue
2022
10.1109/TGRS.2021.3051799
IEEE Transactions on Geoscience and Remote Sensing
Keywords
DocType
Volume
Active–passive fusion,aerosol optical depth (AOD) recovery,Bayesian maximum entropy,large scale,Moderate Resolution Imaging Spectroradiometer (MODIS)
Journal
60
ISSN
Citations 
PageRank 
0196-2892
0
0.34
References 
Authors
0
13
Name
Order
Citations
PageRank
Xinghui Xia100.34
Bin Zhao200.34
Tianhao Zhang301.35
Luyao Wang400.68
Yu Gu500.34
Kuo-Nan Liou600.34
Feiyue Mao732.58
Boming Liu822.21
Yanchen Bo9166.61
Yusi Huang1010.77
Jiadan Dong1100.68
Wei Gong1210432.67
Zhongmin Zhu1300.68