Classify Air Points
Summary
This function classifies points that are significantly higher than the surrounding points into airborne noise points. The idea of the algorithm is the same as the principle of Outlier Removal in the data management module.
Usage
Click Classify > Classify Air Points
Settings
- Input Data: The input file can be a single point cloud data or a point cloud dataset, which must be opened in the LiDAR360 software.
- From Class: Source class(es).
- To Class: Target class.
- Neighbor Points (default value is"10"): The number of neighbors that will be used to determine whether a point is a noise in the sky. Calculate the distance between each point to the nearest point and calculate the standard deviation of the nearest distances.
- Multiples of std deviation (default value is"5"): If the deviation of points beyond the minimum allowable threshold, they are considered as noise in the sky. The larger the threshold, the less the noise will be divided into.
- DefaultValue: Click this button to set all parameters as default.