Quality Improvement of Atmospheric Correction Products of MODIS with HJ-1A/B Satellite CCD Images

For the highly turbid waters along the China coastal region,MODIS atmospheric correction products derived using shortwave infrared(SWIR) bands always have signal saturation and stripe noise.We demonstrate an improvement method with neural network for MODIS/Terra atmospheric correction products using quasi-synchronization HJ-1A/B satellites CCD images and in-situ data.The average relative error of the improved Rrs and MODIS Rrs is 13.3% and the average relative error of the improved Rrs in signal saturation area and in-situ data is 28.2%.The results show that this method is an effective way to significantly repair the blank area in the MODIS/Terra products and remove the stripe noise with acceptable error.