Journal of Geo-information Science ›› 2020, Vol. 22 ›› Issue (9): 1887-1896.doi: 10.12082/dqxxkx.2020.190206

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Retrieval of Aerosol Optical Depth Using FY3D MERSI2 Data

CHEN Hui(), LI Qing, WANG Zhongting, MA Pengfei, LI Ying*(), ZHAO Aimei   

  1. Satellite Environment Center, Ministry of Ecology and Environmental, Beijing 100094, China
  • Received:2019-05-05 Revised:2020-01-06 Online:2020-09-25 Published:2020-11-25
  • Contact: LI Ying E-mail:matheking@163.com;trunks02029@163.com
  • Supported by:
    National Environmental Protection Standard Preparation and Revision Project(2017-27);Causes of Heavy Air Pollution and Tackling Key Problems(DQGG0205)

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