Steep terrain affects optical satellite images through variations it creates in both irradiance and bidirectional reflectance distribution function (BRDF) effects. To obtain the corrected land surface reflectance and detect land surface change through time series analysis over rugged surfaces, it is necessary to remove or reduce the topographic effects. In this paper a physics-based BRDF and atmospheric correction model that handles both flat and inclined surfaces in conjunction with a 1-second SRTM (Shuttle Radar Topographic Mission) derived Digital Surface Model (DSM) product was applied to 8 Landsat scenes covering different seasons and terrain types in eastern Australia. Visual assessment showed that the algorithm removed much of the topographic effect and detected deep shadows in all 8 images. An indirect validation based on the change in correlation between the data and terrain slope showed that the correlation coefficient between the surface reflectance factor and the cosine of the incident (sun) angle reduced dramatically after the topographic correction algorithm was applied. The correlation coefficient typically reduced from 0.80–0.70 to 0.05 in areas of significant relief. It was also shown how the terrain corrected surface reflectance can provide suitable input data for multi-temporal land cover classification in areas of high relief based on spectral signatures and spectral albedo, while the products based only on BRDF and atmospheric correction cannot. To provide comparison with previous work and to validate the proposed algorithm, two empirical methods based on the C-correction were used as well as the established SCS-method to provide benchmarks. The proposed method was found to achieve the same measures of shade reduction without empirical regression.