3D Reconstruction of Buildings From Classified LiDAR Point Cloud

3D reconstruction of buildings from LiDAR point cloud is the creation of three dimensional building models from LiDAR point cloud. The aim of this study was to reconstruct 3d building models from LiDAR point cloud. Three datasets, each with different point densities were used and micro-station software was utilized for 3d reconstruction in this study. Two approaches were adopted for the purpose of reconstruction methodology that is automatic and half automatic approach. These two approaches were conducted for the three different datasets and their results were analyzed. Different tools that can be used for the editing of models were analyzed and changes occurred by varying different parameters were also noted. The data set with higher point density gave a very good model in automatic approach without much manual interventions, but as the point density decreased automatic method was not feasible. As a result half automatic method was implemented and more manual effort during this approach gave better results. This study proved that 3D reconstruction of buildings from LiDAR point cloud can be easily done using micro-station if the density of the point cloud is higher but for LiDAR datasets with less number of points lot of manual work is essential and also additional data like orthophotos are essential for the proper reconstruction of buildings.