LiDAR and SfM point cloud fusion effects in the generation of urban Digital Surface Models
Keywords:LiDAR, SfM, ICP, Fractal Dimensions,, terrain roughness Index
Unmanned Aerial Vehicles with Light Detection and Ranging (LiDAR) scanners
provide a relatively very accurate 3D point cloud, opposed passive imaging
photogrammetry cameras deriving a more detailed 3D model of the real world.
This paper investigates the difference between active and passive drone
photogrammetry based Digital Surface Model of an urban area and tests the
morphometric surface parameters.
The workflow consists of three processing steps. First, a real-time kinematic
unmanned aerial vehicle flight for LIDAR scanning and photogrammetry image
capturing. Then, aerial image processing for dense point clouds generation and
fusion. Finally, to make a comprehensive and fair comparison between
datasets, a geomorphometry qualitative and quantitative analysis of the
texture. Fractal dimensions and Topographic Roughness Index have been
applied to evaluate LiDAR, Structure from Motion photogrammetry and the
fusion DSMs in terms of visualization and statistical analysis.
The results demonstrate the importance of point cloud fusion for the
enhancement and improvement of the DSM quality in urban areas.
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