A Quantitative Assessment Framework for Ground Control Point Spatial Distribution in UAV Photogrammetry Based on Dual-Uniformity Evaluation—A Case Study of Mengshan Hilly Area, China
Abstract
The spatial distribution of ground control points (GCPs) is a critical factor affecting the accuracy of UAV photogrammetry in hilly terrain. In existing studies on GCP distribution, researchers have largely focused on planar uniformity metrics in flat terrain or on the effects of flight parameters in mountainous areas, with limited attention to the distinct roles of horizontal and vertical placement. In this study, we utilized a consumer-grade RTK-equipped UAV to acquire aerial imagery in a typical hilly area, with 27 high-precision GCPs deployed as a reference dataset. Four comparative experiments combining random/uniform distributions in both horizontal and vertical dimensions were designed to quantitatively analyze the impact of different distribution patterns on aerial triangulation and mapping accuracy. Our results demonstrate that the dual-uniform distribution strategy (i.e., uniform in both planimetric layout and elevation stratification) achieves the highest accuracy among the four tested configurations, with horizontal RMSE of 0.045 m and vertical RMSE of 0.039 m. Furthermore, we propose the Spatial Distribution Balance Index (SDBI), which integrates the Planar Uniformity Index (PUI) and Vertical Uniformity Index (VUI) with a terrain-adaptive weighting mechanism. The VUI weight, exemplified as β = 0.714 for this study area via a Sigmoid nonlinear amplification function (k = 15, x0 = 0.15), enables the SDBI to adaptively reflect terrain sensitivity to vertical control. The enhanced SDBI exhibits a correlation coefficient of r = −0.93 with final accuracy, validating its effectiveness as a GCP layout evaluation tool. In this study, we establish the SDBI as a diagnostic metric that quantitatively links GCP distribution characteristics to photogrammetric accuracy outcomes, providing both theoretical insights into anisotropic error propagation and practical guidance for deployment design in hilly regions.