SPECTRAL_PARTITIONING

The SPECTRAL_PARTITIONING command allows for automatic segmentation of points from lidar point clouds using a spectral graph partitioning method. This automatic analysis tool breaks the point cloud into segments based on the spatial and attribute relationships between points returns in the point cloud. The following parameters are supported by the command:

  • FILENAME - filename or description of loaded layer(s) to classify Lidar points in. This parameter can be listed more than once to specify multiple input files, like FILENAME="FILENAME_1" FILENAME="FILENAME_2".
  • LIDAR_RESOLUTION - the distance parameter defining the size of a points local neighborhood which is averaged over to evaluate point attributes and similarity. The value of this parameter can range from 0.0001 to 1000.0
  • LIDAR_RESOLUTION_UNITS - The units used to define the LIDAR_RESOLUTION. Accepted values are POINT SPACINGS, FEET, and METERS. The default value if not specified is LIDAR_RESOLUTION_UNITS="METERS"
  • Attribute Specification - Select attributes used to evaluate the point to point similarity measure that informs spectral partitioning. Attributes of a point are based on statistics of a local neighborhood with extent defined by the resolution. Each attribute is accompanied by a weight which determines its relative contribution to the point similarity measure. All attributes except position are optional and will not be used if not specified. The weight range for each attribute is 0.0 to 1000.0
    • SPECT_PART_POSITION_WEIGHT - position refers to the X/Y/Z or Lat/Lon/Elevation position of each point return. This parameter is required positional relationship between points will always be considered.
    • SPECT_PART_IS_CURVATURE and SPECT_PART_CURVATURE_WEIGHT- when enabled (SPECT_PART_IS_CURVATURE=YES) analyzes the curves created by the points in a local neighborhood.
    • SPECT_PART_IS_NORMAL and SPECT_PART_NORMAL_WEIGHT - when enabled (SPECT_PART_IS_NORMAL=YES) will consider the direction perpendicular to the surface the point is representing.
    • SPECT_PART_IS_RETURN_NUMBER and SPECT_PART_RETURN_NUMBER_WEIGHT - when enabled (SPECT_PART_IS_RETURN_NUMBER=YES) similarity in the return number of each point return in the data set will be considered.
    • SPECT_PART_IS_INTENSITY and SPECT_PART_INTENSITY_WEIGHT - when enabled (SPECT_PART_IS_INTENSITY=YES) the intensity or strength of return will be considered.
    • SPECT_PART_IS_COLOR and SPECT_PART_COLOR_WEIGHT - when enabled (SPECT_PART_IS_COLOR=YES) the applied RGB color of the returns will be considered.
  • SPECT_PART_CONNECTIVITY - threshold value for algebraic connectivity that is used to determine where to cut to divide into segments. A larger value will result in more segments. Acceptable values range from 1e-4 to 100.0
  • SPECT_PART_MAX_CURVATURE - Maximum allowed curvature used to discourage connectivity between points with large curvature over local neighborhood. Acceptable values range from 1e-4 to 180.0
  • LIDAR_MAX_STD_DEV - Point-to-point associations used for clustering are limited to those that are within a specified statistical distance. This threshold reduces processing requirements by ignoring point to point similarity measure above the given value. A larger number of standard deviations will include more weakly connected points in the same segment. A lower value will likely create fewer segments but the points in each will be more closely related. Accepted values range from 0 to 20.0
  • LIDAR_MIN_CLUSTER_SIZE - Minimum number of points a segment must have before being assigned a segment ID. Accepted values range from 1 to 100000