Atmospheric correction is an essential process to correct atmospheric effects in Optical Remote Sensing Data (ORSD) and to provide surface reflectance. The surface reflectance is the most basic and important parameter in optical remote sensing to perform vegetation analysis as well as urban growth assessment. In this study, two atmospheric correction methods, i.e. SREM (Simplified and Robust Surface Reflectance Estimation Method) and 6SV (Second Simulation of the Satellite Signal in the Solar Spectrum, Vector version), were compared over diverse land surfaces using Landsat-8 data. The results showed that the SREM atmospheric correction method performed equally as 6SV over diverse land surfaces. However, the performance of SREM was better than 6SV over hilly terrain as 6SV provides negative values of the surface reflectance due to overcorrection.