Improving Urban Mapping Accuracy: Investigating the Role of Data Acquisition Methods and SfM Processing Modes in UAS-Based Survey Through Explainable AI Metrics

Abstract In this study, we investigated the accuracy of surface models and orthophoto mosaics generated from images acquired using different data acquisition methods at different processing levels in two urban study areas with different characteristics. Experimental investigations employed single- and double-grid flight directions with nadir and tilted (60°) camera angles, alongside the Perimeter 3D method. Three processing levels (low, medium, and high) were applied using SfM software, resulting in 42 models. Ground truth data from RTK GNSS points and aerial LiDAR surveys were used to assess horizontal and vertical accuracies. For the horizontal accuracy test, neither the oblique camera angle nor the double grid resulted in an improvement in accuracy. In contrast, when examining the vertical accuracy, it was concluded that for several processing levels, the tilted camera angle yielded better results, and in these cases, the double grid also improved accuracy. Feature importance analysis revealed that, among the four variables, the data acquisition method was the most important factor affecting accuracy in two out of three cases.