Abstract
Airborne laser scanning sensors are impressive in their ability to collect a large number of topographic points in three dimensions in a very short time thus providing a high-resolution depiction of complex objects in the scanned areas. The quality of any final product naturally depends on the original data and the methods of generating it. Thus, the quality of the data should be evaluated before assessing any of its products. In this research, a detailed evaluation of a LIDAR system is presented, and the quality of the LIDAR data is quantified. This area has been under-emphasized in much of the published work on the applications of airborne laser scanning data. The evaluation is done by field surveying. The results address both the planimetric and the height accuracy of the LIDAR data. The average discrepancy of the LIDAR elevations from the surveyed study area is 0.12 m. In general, the RMSE of the horizontal offsets is approximately 0.50 m. Both relative and absolute height discrepancies of the LIDAR data have two components of variation. The first component is a random short-period variation while the second component has a less significant frequency and depends on the biases in the geo-positioning system.
Subject
General Earth and Planetary Sciences
Reference33 articles.
1. An approach for the precise DEM generation in urban environments using multi-GNSS;Wani;Measurement,2021
2. A literature synthesis of LiDAR applications in transportation: Feature extraction and geometric assessments of highways;Gargoum;GISci. Remote Sens.,2019
3. Kulawiak, M. (2022). A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds. Remote Sens., 14.
4. Lv, D., Ying, X., Cui, Y., Song, J., Qian, K., and Li, M. (2017, January 3–5). Research on the technology of LIDAR data processing. Proceedings of the First International Conference on Electronics Instrumentation and Information Systems (EIIS), Harbin, China.
5. Co-registering satellite images and LIDAR DEMs through straight lines;Elaksher;Int. J. Image Data Fusion,2016
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献