The Key Data Processing Technology And Application Of Terrestrial And Airborne Lidar

Light Detection and Ranging(LiDAR) is an active measuring method which can quickly acquire three dimensional space information of the target. And it has advantages such as all-weather, high precision and low costs. In recent years, Terrestrial LiDAR and Airborne LiDAR have been widely used in the fields as forestry, urban, transportation, hydrographic and so on. This paper aims to study the data processing technology and industrial application of Terrestrial and Airborne LiDAR. Our main goals is to study the data processing and modeling of vegetation biomass estimation, landslide monitoring and building boundary extraction.The main contents and results are as follows:1. The system structure and data acquisition of the Terrestrial LiDAR are introduced. Combing with the needs of vegetation biomass estimation and characteristics of the actual Terrestrial LiDAR data, we design the workflow of processing the Terrestrial LiDAR data. Firstly, we pre-process the Terrestrial LiDAR data and eliminate the errors. Then we filter the data and get the ground points. Finally the non-ground points are pumped sparse and the vegetation points are obtained.2. We study the data processing methods of the Airborne LiDAR data, and focus on the principle and method of classification. A comprehensive analysis of the Airborne LiDAR data classification methods are carried out. Based on the characteristics of the Airborne LiDAR data, we get the classification of buildings, vegetation and arable land.3. Based on the ground and vegetation points processed by the Terrestrial LiDAR data, we extract the vegetation height which is a vertical structure parameter of herbaceous vegetation. The Landsat-8 OLI and Radarsat-2 images are processed to calculate vegetation index and back-scatter-coefficient related to vegetation biomass. We study the principle of BP neural network and optimize the defects. Then we combine these results as the input data of the optimized BP neural network to estimate the vegetation biomass. The result turns out well.4. Based on the classified data of the Airborne LiDAR data, we study the potential application of the Airborne LiDAR on the landslide monitoring and building boundary extraction. Focusing on the Airborne LiDAR data processing for landslide monitoring, we use the classified data to calculate the landslide factors, and use SPSS software for landslide susceptibility analysis, finally obtain the landslide risk evaluation map in Pu Bu Gou Reservoir. Then we study the building boundary extraction method, and give the basic principles and processes for the building boundary extraction, and finally extract the building boundary by using the Alpha-Shapes algorithm.To sums up, through a large number of examples, we study the data processing of Terrestrial and Airborne LiDAR, and use the results in the vegetation biomass estimation, landslide monitoring and building boundary extraction, this paper lays a foundation for further study of LiDAR applications.