期刊
REMOTE SENSING
卷 11, 期 24, 页码 -出版社
MDPI
DOI: 10.3390/rs11243019
关键词
UAS; drones; lidar; targets; accuracy; calibration; adjustment
类别
资金
- United States Department of Commerce-National Oceanic and Atmospheric Administration (NOAA) through The University of Southern Mississippi [NA18NOS400198]
- USDA National Institute of Food and Agriculture, McIntire Stennis project [FLA-FOR-005305]
- U.S. Geological Survey [300]
Lidar from small unoccupied aerial systems (UAS) is a viable method for collecting geospatial data associated with a wide variety of applications. Point clouds from UAS lidar require a means for accuracy assessment, calibration, and adjustment. In order to carry out these procedures, specific locations within the point cloud must be precisely found. To do this, artificial targets may be used for rural settings, or anywhere there is a lack of identifiable and measurable features in the scene. This paper presents the design of lidar targets for precise location based on geometric structure. The targets and associated mensuration algorithm were tested in two scenarios to investigate their performance under different point densities, and different levels of algorithmic rigor. The results show that the targets can be accurately located within point clouds from typical scanning parameters to < 2 cm sigma, and that including observation weights in the algorithm based on propagated point position uncertainty leads to more accurate results.
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