基于静止卫星GOCI传感器的大气污染过程AOD监测

针对北京及周边地区2017年11月2~8日的一次污染过程，利用韩国静止卫星COMs1GOCI数据，对北京地区进行AOD监测.AOD反演采用时间序列迭代算法，根据地表反射率随时间慢变而大气气溶胶随时间快变的理论，采取最小值拟合的方式，获取气溶胶光学厚度数据.反演结果与地基AERONET监测结果具有很好的一致性，两者的相关系数R²大于0.89.AOD监测结果表明，GOCI传感器1次/h的监测频率，可以很好地展现北京地区大气污染过程的开始，发展及消散过程，可以展示出一天之内AOD的变化，为大气污染监测以及气候变化研究提供依据.

An AOD monitoring of air pollution process based on GOCI data

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.