Exercise 2. Diameter at Breast Height (DBH)

This exercise will explore ways to measure Diameter at Breast Height (DBH) of individual trees using the TLS Forest module’s TLS Editor. The input dataset should be a normalized TLS point cloud generated by following steps identified in the previous exercise. Please use the sample dataset TLSData_Remove Outliers_Normalize by Ground Points.LiData created in Exercise 1 or the version found in the sample data folder for this tutorial.

TLS Editor

The TLS Editor can be used to add or delete point cloud segmentation Seed Points, to execute point cloud segmentation operations that include Seed Points, and to measure physical attributes of individual trees, such as DBH, found in the segmented point cloud. Detailed introductions to methodologies and parameters underlying the tools highlighted in this section are available in the LiDAR360 User Guide: TLS Editor.

  • Seed Point: a seed point is the location point of a tree. This point is used as the starting point of ‘growing’ a tree in the tree segmentation algorithm. In TLS module, seed point should be the xyz location of the tree at breast height.

1 Go to TLS Forest > TLS Editor. The TLS Editor toolbar will appear in your window viewer.

2 On the toolbar, go to Editor > Start Edit. Select your normalized point cloud to edit and click OK.

3 In the Setting window, leave both Parameter Setting and Display Setting as default and click OK.

Parameter Setting

  • Show Point Cloud Height: Min Height and Max Height define the points between which that will be sliced and displayed in TLS Editor View Window.

DBH Setting

  • Min DBH, Max DBH: Fitted DBH values falling outside the min-max DBH range will be excluded from the results.
  • Minimum angle between tree and ground: If the angle between a candidate tree point and the nearest ground point is smaller than this value, the point will not be treated as part of the tree. The default value is 30°.
LiDAR360 TLS Forest

Note that if the min-max height range is greater than 0.4 m when fitting DBH in Batch Extraction mode, LiDAR360 will use a stricter method to estimate the confidence level. This method usually performs better for trees with long trunks (the length between bottom of the tree and the first branch).

  • Confidence Level: after fitting DBH, the algorithm will aggregate several statistics such as fitting certainty of tree trunk and DBH circle to categorize fitting confidence into three levels: Low, Medium, High.
LiDAR360 TLS Forest

Batch Extraction of DBH

4 Click on Batch Extraction DBH tool . In the Batch Extraction DBH window, click OK to fit DBH measurements to each tree the tool identifies. Alternatively, users can first select regions of the input point cloud using the TLS Editor’s selection tools (Circle Selection, Rectangular Selection, and Polygon Selection tools). Then, before running the Batch Extraction DBH tool, check Selected Only option to fit DBH values for trees falling within selected regions of the input point cloud.

LiDAR360 TLS Forest

The fitted DBH values will be displayed in the TLS Editor viewer as bisected circular markers centered at the locations of individual trees. Each circular marker will have two numeric labels associated with it: (1) a Tree ID integer value and (2) an extracted DBH measurement value given in meters with sub-centimeter level precision. Use Setting to control the visibility options for the labels and individual tree markers (Seed Setting).

LiDAR360 TLS Forest
Fitted-DBH values symbolized by bisected circular markers labelled with an ID

Inspect and Edit Results

5 To inspect and edit fitted DBH outputs from the Batch Extraction DBH tool, click on Filter Trees and choose desired parameters among Confidence Level, Tree ID, DBH, and Tree Height to filter the trees with. Set Confidence Level to Low and click Apply.

In this instance, trees of Tree IDs 5, 34, and 37 meet the filter parameters.

LiDAR360 TLS Forest
Fitted DBH values for which a low confidence level exists have been selected using the TLS Editor’s Tree Filter and are displayed here in red.

6 Draw 3D profile views with Profile tool to examine the fitted DBH values for which low Confidence Levels exist.

In this instance below, the DBH value for Tree ID 37 was obviously fitted incorrectly.

LiDAR360 TLS Forest
Fitted DBH value selected in the 2D viewer (left), while points within the red hexagonal selection object are displayed in 3D viewer (right)

7 Switch the data selection target to be Seed Points , then use the TLS Editor selection tools (Circle Selection, Rectangular Selection, and Polygon Selection) to select the incorrect seed point in the main or profile display. Once selected, the Seed Points will be highlighted in cyan.

LiDAR360 TLS Forest
Selected Seed Point is highlighted in both the 2D and 3D viewers

8 Use Delete Seed Points or hit the Delete key on the keyboard to remove the selected seed point.

Alternatively, users can choose to delete all DBH values of Low Confidence Level in the Tree Filter window by choosing Delete, checking Low, and then Apply.

LiDAR360 TLS Forest

9 Examine the rest of the DBH values of Confidence Levels Middle and High to check for errors in the results.

10 To run DBH fitting on a different subset of the point cloud data, first switch selection target to Point Cloud , and then use the selection tools to select point cloud data for the area of interest. Selected points will then be highlight in red in the TLS Editor view windows.

LiDAR360 TLS Forest
Selected points are highlighted in the TLS Editor 2D and 3D viewers in red

Click Fit DBH tool to fit a DBH value to a set of selected points representing a single tree. Results of High Confidence Level will display in yellow.

LiDAR360 TLS Forest
DHB fitting tool results for which a high confidence level in the extracted value exists.

11 Use the Pan Profile tool to move the profile view around to inspect, delete, or remeasure all DBH values fitted to the input point cloud or Seed Points.

12 Once the fit-DBH values are determined to be satisfactory, go to Editor > Save Seed Points File and save the results as a .CSV file. The .CSV should have five columns: TreeID, TreeLocationX, TreeLocationY, TreeLocationZ, and DBH. This .CSV file will be used as an input for Point Cloud Segmentation from Seed Points in the next exercise.

LiDAR360 TLS Forest

13 End Edit before continuing on in this tutorial.

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