Electromagnetic radiance acquired by sensors is distorted mainly by atmospheric absorbing and scattering. Atmospheric
correction is required for quantitatively analysis of remote sensing information. Radiation transfer model based
atmospheric correction usually needs some atmospheric parameters to be chosen and estimated reasonably in advance
when atmospheric observation data is lacked. In our work, a radiometric calibration was applied on the satellite data
using revised coefficients at first. Then several parameters were determined for the correction process, taking into
account the earth's surface and atmospheric properties of the study area. Moreover, the atmospheric correction was
implemented using 6S code and the surface reflectance was retrieved. Lastly, the influence of atmospheric correction on
spectral response characteristics of different land covers was discussed in respects of the spectral response curve, NDVI
and the classification process, respectively. The results showed that the reflectance of all land covers decreases evidently
in three visible bands, but increases in the near-infrared and shortwave infrared bands after atmospheric correction.
NDVI of land covers also increases obviously after atmospheric influence was removed, and NDVI derived from the
surface reflectance is the highest comparing to that from the original digital number and the top of atmosphere
reflectance. The accuracy of the supervised classification is improved greatly, which is up to 87.23%, after the
atmospheric effect is corrected. Methods of the parameter determination can be used for reference in similar studies.