Retrieval System of Aerosol Optical Depth Based on High Spatio-Temporal Resolution Satellite Data

Abstract

Abstract:

Satellite remote sensing is a useful and important tool to monitor the aerosol temporal and spatial changes. GF-4 satellite is a new generation geostationary satellite which has more spectral bands in visible to near infrared spectrum and high spatio-temporal resolution. GF-4 grabs images in fo-cusing and scanning observation modes. So GF-4 characteristics create a good condition for aerosol monitoring. Utilizing the ultra-high spatio-temporal resolution satellite data acquired by GF-4, an operational software system was designed to retrieve aerosol optical depth. The characteristics of GF-4 observation modes and the sensibility of sensor bands to aerosol retrieval were investigated. The retrieval algorithm of aerosol optical depth was developed for ultra-high spatio-temporal resolution satellite data of GF-4, with a core idea of time-varying difference of reflectance etween surface and atmosphere special for geostationary satellite. Then, an operational software system was developed. The software system has the capabilities of multithreading calculation and automatic operation, which meet the demands of satellite data operational processing. A series of GF-4 sat-ellite data were processed and validated by the ground-based experimental data, which can be got from the ground-based aerosol observation network. Preliminary results were obtained and indicate that the system has good reliability and stability. This remote sensing software system can be useful to monitor spatio-temporal changes of atmospheric particulates.

Key words: ultra-high spatio-temporal resolution, time-varying difference of reflectance etween surface and atmosphere, aerosol optical depth, remote sensing retrieval system

CLC Number:

YANG Jiu-Chun, LI Zheng-Jiang, CHEN Xin-Feng, LI Bao-Sheng, HOU Wei-Zhen, DIAO Shao-Shuai, GE Bang-Yu, MA Yan, ZHANG ang. Retrieval System of Aerosol Optical Depth Based on High Spatio-Temporal Resolution Satellite Data[J]. Journal of Atmospheric and Environmental Optics, 2018, 13(2): 112-120.

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