Innovative 3D Geometric Modeling of Urban Buildings Using Airborne Lidar Point Cloud Data and Imaging: Applications in Biotechnological Urban Planning

Abstract

Urban buildings play a critical role in city planning and development. Enhanced three-dimensional (3D) geometric modeling of these structures is pivotal for advancing digital urbanization efforts. This research focuses on improving the accuracy of 3D geometric modeling of urban buildings by integrating airborne LiDAR (Light Detection and Ranging) point cloud data with oblique imaging techniques. The methodology involves a sophisticated two-tier grid filtering process to eliminate gross errors from LiDAR data, followed by morphological filtering to refine the data quality. Additionally, the spatial geolocation information is reconstructed using tilt photogrammetry technology, enhancing the precision in modeling. The process further includes extracting distinct architectural features such as step lines and roof patches from the urban building point cloud. These features are then accurately registered and positioned using the oblique images, which also facilitate the integration of textural details into the model, thus achieving a comprehensive 3D geometric representation of urban structures. The combined use of LiDAR and image data not only enriches the model's detail but also significantly boosts the accuracy and efficiency of the modeling process. Experimental results validate the effectiveness of the proposed method, demonstrating its ability to accurately reflect the spatial layout of urban environments and substantially improve both the precision and operational efficiency of 3D geometric modeling. This approach, with its detailed and accurate modeling capabilities, has profound implications for biotechnological applications in urban planning, providing essential data that can be used to optimize ecological and environmental aspects of urban design.