Evaluating Smartphone LiDAR for Road Infrastructure Mapping: Harmonisation of iPhone LiDAR Data with National Airborne LiDAR Datasets

Abstract. National airborne laser-scanning campaigns, such as the Dutch AHN update, run on multi-year cycles, leaving newly built infrastructure undocumented for years. This study investigates whether smartphone LiDAR can close that gap by harmonising iPhone-acquired point clouds with the national dataset, using road markings as shared geometric reference features. A four-stage workflow is proposed: data acquisition, road-marking extraction, transformation from a local to the national reference frame, and voxel-based harmonisation, demonstrated on a simulated highway ramp at the Future Mobility Park in Rotterdam using an iPhone 17 Pro and two free acquisition packages, RDTAB (S1) and Modelar (S2). Variations in acquired data volume and preprocessing between the packages helped assess harmonisation with the national point cloud, based on the resulting points, RGB values, and spatial distribution. The case study showed registration accuracies of 0.039 m and 0.164 m against GNSS control points, with positioning error as the main factor affecting altimetric accuracy, which ranged from 0.053 to 0.170 m. The average ICP cloud-to-cloud difference across both packages and the national point clouds was 0.032 m. These results indicate that smartphone LiDAR is accurate and low-cost enough to serve as a complementary, not alternative, data source for high-frequency updates between national mapping campaigns.