Abstract
Current reported spatiotemporal solutions for fusing multisensor aerosol optical depth (AOD) products used to recover gaps either suffer from unacceptable accuracy levels, i.e., fixed rank smooth (FRS), or high time costs, i.e., Bayesian maximum entropy (BME). This problem is generally more serious when dealing with multiple AOD products in a long time series or over large geographic areas. This study proposes a new, effective, and efficient enhanced FRS method (FRS-EE) to fuse satellite AOD products with uncertainty constraints. AOD products used in the fusion experiment include Moderate Resolution Imaging SpectroRadiometer (MODIS) DB/DT_DB_Combined AOD and Multiangle Imaging SpectroRadiometer (MISR) AOD across mainland China from 2016 to 2017. Results show that the average completeness of original, initial FRS fused, and FRS-EE fused AODs with uncertainty constraints are 22.80%, 95.18%, and 65.84%, respectively. Although the correlation coefficient (R = 0.77), root mean square error (RMSE = 0.30), and mean bias (Bias = 0.023) of the initial FRS fused AODs are relatively lower than those of original AODs compared to Aerosol Robotic Network (AERONET) AOD records, the accuracy of FRS-EE fused AODs, which are R = 0.88, RMSE = 0.20, and Bias = 0.022, is obviously improved. More importantly, in regions with fully missing original AODs, the accuracy of FRS-EE fused AODs is close to that of original AODs in regions with valid retrievals. Meanwhile, the time cost of FRS-EE for AOD fusion was only 2.91 h; obviously lower than the 30.46 months taken for BME.
Highlights
Aerosol particles suspended in the air are some of the main pollutants that affect human health [1,2,3]
The popular ones are the Moderate Resolution Imaging Spectro-Radiometer (MODIS) and the Multi-angle Imaging Spectro-Radiometer (MISR). While these two satellite sensors have provided many aerosol optical depth (AOD) products for air quality assessment so far [5,6], their AODs are usually missing over space, due to the limited swath width, the influences of cloud cover, and the theoretically inherent limitations of AOD retrieval algorithms [7]
This section will only briefly introduce the fixed rank smooth (FRS) model and the fusion framework for various satellite AOD products based on the proposed FRS-EE method
Summary
Aerosol particles suspended in the air are some of the main pollutants that affect human health [1,2,3]. Ground-based measurements and satellite retrievals of aerosol optical depth (AOD) are, becoming important ways to indirectly assess air quality [4]. Satellite retrievals can obtain AODs with large spatial coverage and this method has more applications than ground-based measurements. The popular ones are the Moderate Resolution Imaging Spectro-Radiometer (MODIS) and the Multi-angle Imaging Spectro-Radiometer (MISR). While these two satellite sensors have provided many AOD products for air quality assessment so far [5,6], their AODs are usually missing over space, due to the limited swath width, the influences of cloud cover, and the theoretically inherent limitations of AOD retrieval algorithms [7]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
