The annual Survey School Research Symposium and Competition brings together the next generation of geospatial innovators to bridge traditional fieldwork with advanced tech like LiDAR and photogrammetry. This year's winning presenter will break down their groundbreaking research, showcasing a high-precision, real-world application that perfectly balances cutting-edge geospatial workflows with strict survey-grade accuracy. Attendees will gain a direct look into the exact methodologies, field challenges, and data processing techniques that set the standard for the future of the geomatics industry.

Professional mobile mapping systems achieve centimeter-level accuracy through the tight integration of navigation-grade IMUs, survey-grade GNSS, and calibrated laser scanners. This paper assesses the relative and absolute accuracy of a vehicle-mounted test platform that combines a NovAtel SPAN tightly coupled GNSS/IMU with a mid-grade Velodyne VLP-16 LiDAR, evaluated along a 1.2 km test loop on The Ohio State University campus. The mobile-cloud georeferencing is driven entirely by the SPAN-processed GNSS/IMU trajectory, post-processed in NovAtel Inertial Explorer; three additional survey-grade PPK GNSS receivers are processed independently and serve as cross-checks on the trajectory. Direct georeferencing is performed in the standard ECEF formulation with per-point trajectory interpolation. An independent reference point cloud of the same area is acquired with a Leica RTC360 terrestrial laser scanner, registered and tied down to GNSS-derived ground control so that the TLS cloud carries an independent absolute geodetic datum. Absolute accuracy is then evaluated directly: identifiable features on building façades are coordinated independently in each cloud, and the coordinate differences between the mobile-cloud and TLS positions of the same features quantify the absolute georeferencing error of the directly georeferenced mobile cloud. Relative accuracy is evaluated separately from the internal geometry of each cloud: structure dimensions, inter-feature distances, and inter-feature angles are measured in the mobile cloud and in the TLS and compared, isolating the shape-preservation performance of the platform from any constant offset between the two reference frames. An auxiliary SHARE SLAM S20 handheld scanner mounted on the same vehicle is described as supplementary platform context; its data is not used in the accuracy assessment due to unreliable GNSS/IMU/SLAM integration at vehicle speeds.