Comparison and utilization of point cloud generated from photogrammetry and laser scanning: 3D world model for smart heavy equipment planning

Abstract

Inaccurate information regarding the terrain in construction projects represents a major challenge to the earthwork process. Both construction quality and productivity have to be addressed by means of efficient construction information management in large earthwork projects in order to ultimately improve the cost-effectiveness of such projects. Research into the technologies for creating precise three-dimensional data and maps of earthwork sites is progressing steadily. These technologies aim to make it possible to conduct unmanned operations, leading to the effective management of earth working equipment. In recent years, as the importance of three-dimensional (3D) shape information management has grown in the construction industry, the research and application of 3D point cloud acquisition methods has likewise increased. The current method for acquiring point cloud data through laser scanning renders it difficult to acquire point clouds in large construction projects, especially in earthwork projects, due to the topographic conditions of the site as well as the physical and material limitations of the laser scanning equipment. In order to overcome and compensate for the limitations of laser scanning, image-processing technology involving unmanned aerial vehicles (UAVs) has been used to acquire point cloud data, although its application has been limited due to its low accuracy. Therefore, this study proposed a method for generating and merging hybrid point cloud data acquired from laser scanning and UAV-based image processing. In addition, a comparison was conducted between the datasets acquired from laser scanning and image processing, using examples from some case studies. Finally, an analytical comparison was performed to verify the accuracy of the UAV-based image processing technology for earthwork projects.