Retrieval Of Aerosol Optical Depth Using Domestic Remote Sensing Data Over Beijing

With the rapid industrialization and urbanization, air pollution becomes an increasingly serious problem and has attracted special attention throughout the society. Aerosol optical depth (AOD) is a key indicator of the atmospheric environment. It has great significance to obtain the spatial distribution information of AOD for atmosphere monitoring and pollution controlling. Satellite remote sensing has been an improtant method of AOD monitoring, which can provide spatially continuous information over large areas and frequent time intervals. With the rapid development of China’s remote sensing satellite, several domestic satellites with medium or high resolution sensors were launched in recent years. It is of great significance to carry out research on retrieving AOD by these domestic satellite data. In this paper, HJ-1A/B/CCD, GF-1/WFV and CBERS-04/WFI were employed to retrieve AOD based on deep blue algorithm over Beijing.Data pre-processing is an important part of this paper, including pre-processing for remote sensing data and calculating necessary parameters. The parameters of domestic satellite data are not enough for AOD retrieval. The ESUNb (Mean solar exoatmospheric irradiances over band) for CBERS-04/WFI is not provided yet and need to be calculated before retrieving AOD. Extraterrestrial Solar Spectral Irradiance and Spectral Response Function (SRF) are necessary to calculate ESUNb. Nine released solar spectra and a number of medium spatial resolution sensors whose ESUNb had been officially released were chosen to determine the optimal solar spectra for medium resolution sensors. Then the ESUNb for CBERS-04/WFI were calculated. The data pre-processing for remote sensing data including radiometric calibration, re-projecting, cloud removing and computing viewing geometry et al. For CBERS-04/WFV and HJ-1A/B CCD1 data, the viewing zenith and viewing azimuth were provided officially. However, GF-1/WFV has not provide viewing geometry files. By analysing the geometry information of the four WFV sensors and the viewing angle for central pixels which can be obtain from the header files of the image, the pixel-by-pixel viewing angles were calculated.One of the key steps in retrieving AOD by deep blue algorithm is generating the land surface reflectance database for domestic sensors. There are some differences between the spectral responses of CBERS-04/WFV, GF-1/WFV, HJ-1A/B CCD1 and MODIS.22 spectral data were selected from ENVI standard spectral library to derive the linear relationships between domestic sensors and MODIS. Based on the linear equations, the MODIS land surface reflectance was converted to domestic sensors. Besides, the lookup Tables (LUT) were generated using Second Simulation of the Satellite Signal in the Solar Spectrum (6S) model for each sensors. Based on the LUTs and land surface reflectance database, the AODs were retrieved using deep blue algorithm.The accuracy of retrieved AOD was assessed by AERONET ground observed data. Result indicated that the AOD result of CBERS-04/WFI and HJ-1/CCD1 showed significant correlations with AERONET data (P<0.01), with correlation coefficients of 0.941 and 0.919 respectively. There was less validation samples of GF-1/WFV, which gave a MAE (mean absolute error) value of 0.07. In addition, the AOD results were also compared with MODIS AOD product (MOD04). Result suggested notable correlations between retrieved AOD of three domestic sensors and MODIS AOD (P<0.01). The highest correlation was observed between the retrieved AOD of HJ-1/CCD and MODIS AOD, with the correlation coefficient of 0.931. CBERS-04/WFI achieved the second higher correlation coefficient of 0.863. GF-1/WFV showed the lowest correlation coefficient of 0.590. The satisfactory validation results demonstrated the validity and reliability of the retrieved AOD from domestic satellite data in this paper.