Buildings Based On Airborne LiDAR Point Cloud Data Extraction And Modeling Study

The building is the most important element in the city, and modeling of buildings in urbanareas has important significance for the establishment of digital cities. Airborne LiDARdevelopment of measurement techniques for urban spatial information of a new technical meansto get airborne LiDAR point cloud data, which contains a large number of buildings of spatialinformation, especially as a result of airborne LiDAR works, the building has a lot of richinformation of the roof of a building information. Airborne laser radar development provides astrong support for the modeling demand for digital city buildings.The authors make a description of airborne laser radar technology development, thecharacteristics of the data, domestic and international developments and future trends and thebuildings on the the buildings point cloud data extraction and reconstruction theory.The specificcontent of this article is as follows:Pretreatment of the raw data, culling, filtering and extraction the buildings point threeprocess, including errors point to prepare in advance, after a short walk to the back of thebuilding point pretreatment good work.Clustering method regional growth point cloud of groups of buildings divided between thebuildings and the buildings can not be destroyed, there are errors and other reasons the process ofexcluding non-building data points, each building is divided into separate buildingsof theexisting ray method to improve the use of artificial the error segmentation buildings again thevisual judgments segmentation.Convex hull algorithm, the improved algorithm for point cloud data of buildings surroundedby shell point, and point connections and regularization generate regular boundary contour of thebuilding.In addition to the flat-topped houses, the top of the building is usually formed by a numberof surface, build a simple model of the building will need to determine the point of the surface ofthe roof of a building piece vesting category text to improve existing triangular mesh Vector, thepoint of the dough piece category classification to obtain good results.The least squares method, for each building belong to one facet of the point cloud fitting theequation of the top surface of sheet to strike the linear equation of the intersection plane,combined with the regular contour and a projection theory seeking a feature point of thebuilding. This article in accordance with the procedure set out above, on top of the flat-toppedbuildings as well as the word, four top of the hill, L-shaped human word top simple buildingsconstructed model, and achieve better results.