Abstract
The land topography and urban area digitization in the form of point clouds has become an indispensable method for providing many related services. Aerial point cloud measurements are made using active LiDAR or dense matching photogrammetry methods. Aerial LiDAR and dense image matching point clouds are obtained directly in the geodetic coordinate system thanks to navigation data. The geo-referencing based on ground control points require more labour and work time. All kinds of geometric and semantic information about the terrain can be extracted from the point cloud data. Therefore, it should have both location and visualization accuracy. The detection and definition accuracies of image area details depend on the scanning point density and its uniform distribution. In this study, after having been introduced the parameters of the aerial point cloud related to topographic measurement and urban area modelling, a comparison of these two source point clouds was made in areas with different land cover. The registration of a dense matching point cloud into a geospatial reference system was done with flight data and LiDAR measurements. As consequence, The LiDAR point density depends on the min angular step of the instrument scanning light, while the dense matching is relating to ground sampled distance of pixels.