This article summarizes the five application directions of point cloud data, hope it can bring you help.
Through automatic preprocessing of point cloud data, ground filtering, combined with manual editing, the laser point cloud is further finely classified, the ground points are retained, and the remaining ground points are rasterized by building a model such as an irregular triangular network (TIN). High-precision digital elevation model (DEM) data can be obtained, and can also be converted into contour data.
With the gradual maturity of lidar technology, the 3D model produced by 3D lidar technology has high precision, wide application range, less field work, and saves time and effort. It has played an important role in building outline extraction, feature point detection and 3D reconstruction. And combined with oblique photography technology, the extraction of ground objects is more convenient, and the degree of data visualization is higher.
Airborne laser point clouds can be used to census tree characteristics, such as average tree height, canopy density, biomass, tree stock, and vegetation coverage. If paired with a hyperspectral imager, more information can be determined, such as vegetation classification, vegetation stock, soil changes, etc. Second, derived data can be used to monitor forest growth, damage from storms or fires, and more.
High-precision laser point cloud can be used to build a 3D terrain model, and provide cross-section measurement, slope vector measurement, earthwork filling and excavation volume and other information for survey and design, greatly reducing the field workload and shortening the work cycle in engineering survey and design.
Through the establishment of the three-dimensional model of the terrain, the change of the terrain can be monitored in a large area, and the risk assessment can be made according to the direction of the terrain change and the amount of the terrain change, so as to provide a basis for preventing the occurrence of geological disasters. For example, monitoring the surface of landslides, especially in areas prone to landslides such as roads and railway tracks under steep slopes, and building houses on slopes, can provide an important basis for inferring the cause and development trend of landslides.