ALS Point Cloud Segmentation from Seed Points
Summary
This function supports batch processing of multiple files. The input data consists of normalized point cloud data and the corresponding seed point files. For seed point file generation, please refer to Generate Seed by CHM和Generate Seed by Layer Stacking。
Usage
Navigate to and click on TLS Forest > Point Cloud Segmentation from Seed Points.
Parameters
- 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.- Height Above Ground (meter)(default value is "2"): 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.
- Output File Format:Select the format of output file, choice including .csv attribute table and tree attribute file.
- 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.
- DefaultValue: Reset each parameter to the default value.
Note：For methods to view segmentation results, please refer to Point Cloud Segmentation Results.