From Flight Planning to Field Reality: UAV LiDAR Point Density Requirements for Scale-Consistent 3D Geovisualizations

This study examines the link between drone airborne LiDAR point cloud density and cartographic scale, addressing the question of what density is required for scale-consistent 3D geovisualizations. Additionally, it seeks to address the discrepancy between theoretical density-distribution requirements and the actual, spatially non-uniform point distributions that arise from factors such as topography, vegetation, and scanning geometry. The methodology for linking the cartographic scale to the required point density comprised three basic stages. Initially, the required number of points per square meter was theoretically calculated. The next stage involved collecting data from 10 areas/15 acquisitions across Greece and Cyprus, each with distinct topographic and geomorphological characteristics. Additionally, six different data acquisition scenarios in speed and flight height were studied in a selected area. In the third stage, we processed and analyzed the 3D point clouds, calculated their actual density, compared the values, and developed a geovisualization in a virtual reality environment. The results showed significant deviations between expected and actual density, ranging from −49.3% to +173.8% across the 15 datasets, with 13 of the 15 datasets supporting a finer cartographic scale than planned; they are directly related to topography, vegetation, and scanning geometry, which in turn affect the achievable cartographic scale and the quality of geovisualization. The study provides a validated density-to-scale conversion chain and per-land-cover deviation ranges that can inform adaptive data-collection protocols for reliable cartographic products and 3D realistic geovisualizations.