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An AOD monitoring of air pollution process based on GOCI data |
ZHANG Yu-huan, MAO Hui-qin, LI Qing, WANG Zhong-ting, ZHANG Li-juan, MA Peng-fei, ZHOU Chun-yan, CHEN Hui, CHEN Cui-hong |
Environmental Satellite Application Center, State Environmental Protection Ministry, Beijing 100029, China |
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Abstract An serious air pollution episode over Beijing and surrounding area have persisted from November 2 to 8, 2017. In order to monitor and analyze this air pollution, a remote sensing inversion of time series iterative algorithm (TSIA) was used to retrieval the aerosol optical depth (AOD) for the particle pollutants based on COMs1(Communication、Ocean & Meteorological Satellite-1) GOCI (The Korea Geostationary Ocean Color Imager) data. The core idea of TSIA is the surface reflectance variations is minimized by a reasonable assumption of aerosol changing quickly but earth's surface changing slowly over time. The results show that the AOD over Beijing and around area has a fairly good relationship with R2 of greater than 0.89 compared with the ground-based measurements from Aerosol Robotic NETwork (AERONET). The high monitoring frequency of GOCI (once per hour in daylight) could capture the air pollution trends better from forming to dissipation, which can be of great assistance in climate change researches and environmental monitoring.
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Received: 06 February 2018
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