期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B1
页码：203-210
出版社：Copernicus Publications
摘要：The improving capability of the direct geo-referencing technology is having a positive impact on the widespread adoption of LiDAR systems for the acquisition of dense and accurate surface models over extended areas. A typical LiDAR system consists of three main components: a GPS system to provide position information, an IMU unit for attitude determination, and a laser unit to provide the range (distance) between the laser-beam firing point and the ground point (laser footprint). The measured ranges are coupled with the position and attitude information from the GPS/IMU integration process as well as the bore-sighting parameters relating the system components to derive the ground coordinates of the LiDAR footprints. Unlike photogrammetric techniques, the derivation of the point cloud from the LiDAR measurements is not a transparent process. In other words, the raw system measurements are not always provided to the system user. Moreover, the coordinate computation of the LiDAR footprints is not based on redundant measurements, which are manipulated in an adjustment procedure. Consequently, one does not have the associated measures (e.g., variance component of unit weight and variance-covariance matrices of the derived parameters), which can be used to evaluate the quality of the final product. This paper is concerned with providing a tool for the quality control (QC) of the LiDAR point cloud. The objective of the QC procedure is to verify the accuracy of the LiDAR footprints. In other words, the QC procedure would test whether the expected accuracy has been achieved or not. The paper will start with a brief discussion of the LiDAR mathematical model relating the system measurements to the ground coordinates of the point cloud. Then, an analysis of possible systematic and random errors and their impact on the resulting surface will be outlined. Following the discussion of the error sources and their impact on the accuracy of the LiDAR footprints, a QC tool will be proposed. The paper will conclude by experimental results from a real dataset involving overlapping strips from operational LiDAR system
