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Presenter: Kim Minsu

Conventional approach of representing the absolute accuracy of the lidar point cloud is to provide an absolute accuracy report with RMSEz. It measures statistically significant number of ground checkpoints (x,y,z) and compare to the airborne lidar data. However, the majority of airborne lidar does not easily allow to identify the exact location of corresponding ground check point in the airborne lidar point cloud. Because of the large uncertainty of conjugate point identification, usually only the z values of the checkpoints are compared to the surveyed z values and RMSEz is computed. In order to perform full 3D absolute accuracy assessment including RMSEx and RMSEy, a commonly agreed approach is to use 3D geometry such as 3-plane intersection point. However, there are lots of questions in the implementation of this approach. Depending on the point density, size of the plane, and the precision of the lidar system, the 3-plane intersection point calculation will introduce unacceptably large additional (external) errors on top of the inherent lidar data error that we want to evaluate. This USGS research will illustrate the external uncertainty model that can be used as a guideline to decide the validity condition of 3-plane intersection approach.