Öz
This study aimed to investigate the performance and sensitivity of 3D photogrammetric models generated without GCPs (ground control points). To determine whether the models with no GCPs retained accuracy in all terrain types as well as under varying climate or meteorological conditions, two separate studies were conducted in two areas with different characteristics (elevation, slope, topography, and meteorological differences). The study areas were initially modelled with GCPs and were later modelled without GCPs. Furthermore, some of the dimensions and areas within the modelled regions were measured using terrestrial techniques (with GPS/GNSS) for accuracy analyses. After regional modelling was conducted with and without GCPs, different territories with different slopes and geometric shapes were selected. Various length, area and volume measurements were carried out over the selected territories using both models (generated with and without GCPs). The datasets obtained from the measurement results were compared, and the measurements obtained using the models produced with GCPs were accepted as the true values. The length measurement results provided various levels of success. The first study area exhibited very promising length measurement results, with a relative error less than 1% and an RMSE (root mean square error) of 0.139 m. In the case of the area measurements, in the first study area (Sivas), a minimum relative error of 0.04% and a maximum relative error of 1.05% with an RMSE of 1.264 m² were obtained. In the second study areas (Artvin), a minimum relative error of 0.56% and a maximum relative error of 5.27% with an RMSE of 1.76 m² were achieved. Finally, in the case of the volume measurements, for the first study area (Sivas), a minimum relative error of 0.8% and a maximum relative error of 6.8% as well as an RMSE of 2.301 m³ were calculated. For the second study area (Artvin), the minimum relative error of the volume measurements was 0.502%, and the maximum relative error was 2.01%, with an RMSE of 7.061 m³.