Estimation of variable atmospheric parameters for the atmospheric correction of satellite images

ABSTRACT

The information about variable components of the atmosphere (aerosol, water vapour, and ozone) during acquisition is required for the atmospheric correction of spectral images acquired by shortwave sensors of the Earth observing remote-sensing satellites. The procedure to estimate aerosol optical depth and columnar water vapour by the inversion of the atmospheric radiative transfer model 6S using moderate-resolution spectra of incident solar radiation is proposed. Comparison to the results obtained by the Aerosol Robotic Network AERONET at an AERONET site at the distance of 50 km on days when both sensors were in the same air mass shows systematic overestimation both of aerosol optical depth and of columnar water vapour if aerosol optical depth is estimated in the wavelength range of 365–425 nm and columnar water in the range of 895–985 nm using spectra of total irradiance. If more wavelengths and diffuse-to-total spectral irradiance ratio are implemented in the inversion, the bias of estimated water vapour decreases, but aerosol optical depth is underestimated. The estimates at 50 km distance are well correlated. The modelled spectral irradiance using estimated atmospheric parameters matches the measured spectra with high accuracy. In the spectral bands of the Sentinel-2 MultiSpectral Instrument (MSI), the differences do not exceed 2%.

Acknowledgements

This work was supported by the Estonian Environmental Observatory, Project 3.2.0304.11-0395, by the EU Regional Development Fund, Environmental Conservation and Environmental Technology R&D Programme project BioAtmos (3.2.0802.11-0043), and Targeted financing by the Ministry of Education and Research, Project SF0180009Bs11. We thank Dr Margit Aun and Ilmar Ansko, MSc, for their effort in maintaining the AERONET site at Tõravere.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the EU Regional Development Fund, Environmental Conservation and Environmental Technology R&D Programme project BioAtmos [3.2.0802.11-0043], and Targeted financing by the Ministry of Education and Research [SF0180009Bs11].