Fusion of uav-based lidar and mobile laser scanning data for construction of 3D building model.

Abstract

The necessity for object modelling in the three dimensions (3d) is becoming increasingly critical because of the advantage of presenting information in the natural form. In addition, advancements and sophistication in computer technology, programming, and sensors are driving factors in the growing importance of 3D applications. Building modelling is one of the 3D applications in which the data from the 3D model can support authorities in managing national development. Various techniques have been utilized worldwide to model buildings. The LiDAR system is regarded as one of the best because it generates a very accurate and dense point cloud. Nonetheless, numerous LiDAR systems are available worldwide, and it is possible to integrate different sets of point cloud data from several LiDAR platforms to construct an accurate 3D building model. For that reason, the primary purpose of this research is to generate a 3D building model from point clouds collected by different LiDAR systems. Furthermore, the efficacy of integrating point clouds from different LiDAR systems to construct 3D building models will be explored. This research was conducted inside the Ring Road, UTM, which comprises various objects, including buildings, and has topography with a relatively wide slope variation. Mobile laser scanning and UAV-based LiDAR are different LiDAR systems used in the study area to gather a very dense point cloud of building from differing perspectives. The accuracy of the generated 3D building model has been assessed using the statistical approach known as the RMSE equation. As a result, the 3D building models with RMSE error of ±0.015 meters (planimetric) and ±0.009 (horizontal) were successfully constructed. In conclusion, point clouds from integrated LiDAR systems may produce precise 3D building models.