Abstract: [Purposes]With the growing demand for 3D modeling of dense building areas in architectural planning,there is an urgent need for efficient and high-precision geographic information acquisition and modeling technologies.Oblique photogrammetry technology has blind spots in the 3D modeling of dense building areas,and is particularly prone to model voids and model distortions in areas with vegetation occlusion and weak textures.[Methods]To address the limitations of single-technology modeling,this study adopts unmanned aerial vehicle oblique photogrammetry and LiDAR technology,and conducts 3D real-scene reconstruction through coarse-to-fine point cloud fusion method.[Findings]The results demonstrate that the point cloud fusion technology effectively overcomes the shortcomings of single-data-source modeling: specifically,it improves geometric integrity in complex areas such as those with vegetation occlusion and weak textures,and resolves the issues of model voids and distortions.The generated 3D model has clear textures and accurate geometry,with both its planar accuracy and elevation accuracy stably maintained at the centimeter level.[Conclusions]This method can provide a technical pathway for the fine modeling of dense building areas,and the generated model as well as its derived digital line graphs can also demonstrate good application potential in building cluster planning and spatial analysis.

Key words: LiDAR technology, oblique photogrammetry technology, 3D reconstruction, dense building areas