Satellite images have been widely used in the production of geospatial information such as land use and land cover mapping, as well as the generation of several thematic layers via image processing. Images acquired by sensors onboard various satellite platforms are influenced by systematic sensor and platform-induced geometry errors. Thus, geometric correction of satellite images is an important step of image pre-processing to extract accurate and reliable locational information. Geometric correction of satellite images obtained from two different satellites, Pleiades 1A (PHR) and SPOT-6, was performed within the scope of this study using empirical models and a physical model. The 2D polynomial model, 3D rational function model with calculated RPCs from GCPs, 3D rational function model with RPCs from satellite, RPC refinement model using GCPs, and Toutin's physical model were used within this scope. Several experiments were carried out to investigate the effects of various parameters on the performance of the geometric correction procedure, such as GCP reference data source, GCP number and distribution, DEM source, spatial resolution, and model. Our results showed that lower RMSE values can be achieved with the model that uses RPC from data providers for PHR and SPOT that is followed by the RPC refinement method for PHR and Toutin method for SPOT. In general, GCPs from the HGM data source and ALOS DEM combination provided better results. Lastly, lower RMSE values, thus better locational accuracies are observed with PHR image except for single test.