INTEGRATION OF GNSS AND DRONE-DERIVED HIGH RESOLUTION TOPOGRAPHIC SURVEYS IN ENHANCING HIGHWAY GEOMETRIC DESIGN ACCURACY

Abstract

This study evaluated the integration of Global Navigation Satellite System (GNSS) and drone-derived high-resolution topographic surveys for highway geometric design along the 4.2 km Upper Mission Extension Road, Benin City, Nigeria. A field-based geospatial engineering approach was adopted, with 17 GNSS Ground Control Points established for horizontal and vertical control. A UAV survey covering 101.72 ha was conducted, during which 3,162 aerial images were acquired and processed to generate orthomosaics, dense point clouds, and Digital Terrain Models (DTMs). The integrated GNSS-UAV dataset was used to develop longitudinal profiles, horizontal alignments, vertical curves, and plan-and-profile drawings for highway geometric design. Performance evaluation involved elevation comparison, Root Mean Square Error (RMSE), mean error, standard deviation, point-density analysis, terrain representation, and highway profile assessment. Results from 169 common survey points showed a mean error of −1.366 m, an RMSE of 1.463 m, and a standard deviation of 0.526 m between the GNSS-only and integrated terrain models. The UAV survey achieved an average Ground Sampling Distance (GSD) of 1.89 cm and generated approximately 232.96 million points, corresponding to a point density of 229.02 points/m², compared with only 169 discrete GNSS observations (0.000166 points/m²) over the same area. The integrated approach produced a more continuous and detailed terrain model, enabling improved identification of terrain undulations, enhanced longitudinal profile development, refined vertical alignment design, and more accurate highway geometric design. The study concludes that integrating GNSS with UAV photogrammetry significantly enhances terrain representation and design accuracy and is recommended for future highway rehabilitation and engineering projects.