Point Cloud Segmentation from Seed Points

Summary

The TLS PCS with Seeds function supports batch processing for multiple files. The input data includes normalized point cloud data and the corresponding seed point file. For TLS point cloud normalization, please refer to the Normalize by DEM or Normalize by Ground Points tool section of the LiDAR360 User Manual. For more information on the generation of seed point files, please refer to Batch Extraction DBH tool section of the LiDAR360 User Manual.

Note: Different from Point Cloud Segmentation from Seed Points in ALS Forest tool set, the DBH values are used in Point Cloud Segmentation from Seed Points in TLS Forest tool set. According to the 3D coordinates of the seed points, the algorithm will search for the points within the range of the radius of DBH or the closest point as the original seed points cluster for the following segmentation. If the DBH values are not available here, please set them to 0. For the format information, please refer to Seed Points File.

Usage

Navigate to and click on TLS Forest > Point Cloud Segmentation from Seed Points.

PCS Based on Seed

Settings

  • From Class: Classes which participate in the PCS with seeds (all classes by default).
  • Point Cloud File: Click to select the point cloud data to be processed.
  • Seed File: Click to select the seed file.
  • : Five datasets can be batch processed per tool run. Click to add files to be processed.
  • : Delete the selected point cloud and seed points file.
  • : Clear the file list.
  • Cluster Tolerance (meter)(default value is "0.2"): Users can control the accuracy and efficiency of the individual tree segmentation process by changing this value. Increase of this threshold will result in higher efficiency of the individual tree segmentation process. But if this threshold is too large, it will lower accuracy.
  • Minimum Cluster Size:This parameter will influence the growing of point cloud of individual tree's crown. Fewer points will lead to higher accuracy and lower efficiency. Vice versa.
  • Maximum DBH (meter)(default value is "1.4"): Upper DBH threshold for fitting DBH.
  • Minimum DBH (default value is "1.2"): Lower DBH threshold for fitting DBH.
  • Height Above Ground (meter)(default value is "0.3"): Only the points above this hight will be involved in individual tree segmentation. This parameter is used to decrease the influence of ground points and weeds to the segmentation. It will influence the accuracy of the detection of trunk, if this value is too large.
  • Optimize color rendering for individual tree segmentation result (checked by default): By reorganizing the tree ID generated after the individual tree segmentation, it can greatly solve the problem of rendering the same color to the trees next to each other. Note: if choosing to optimize the color rendering, the tree IDs in new csv file for individual tree segmentation are not one-to-one correspond to those in the input seeds files.
  • Minimum Tree Height (meter)(default value is "2"): Lower threshold of an object which could be recognized as a tree. This is used for filtering out small trees based on the growth rate of the region.
  • Output Path: Path of the output file, which is a comma-separated database table in the .csv format containing the ID of each individual tree identified during the segmentation process, the x, y coordinate of each individual tree, individual tree heights, DBHs, crown diameters, crown areas, and crown volumes. Please refer to Individual Tree Segmentation Result File Format in the appendix.Please refer to

View the Point Cloud Segmentation Results for the steps to view the results.

  • DefaultValue: Reset each parameter to the default value.

results matching ""

    No results matching ""