Our software solution offers a semi-automatic solution for extracting tree parameters from point clouds to build a database of trees with attributes. This solution is rule-based, and does not use any AI features, but provides efficient tools for our users to measure the tree parameters. Our solution is designed mainly for individual trees or lines of trees. Using our toolkit in a forest environment might be challenging.
For this manual, it is recommended to read the Basic Extraction Guide and the Advanced Extraction Guide to ensure the basic knowledge of extraction, clip frame and colouring settings. If there is no schema for the tree attributes, we strongly recommend to read also the attribute structure article for SHP files.
In our case, when we say “tree inventory” or “tree database” we are referring to a SHP file or File Geodatabase, which will store the tree points and attributes the user would like to store about the trees. These formats can be easily appended to any spatial data-compatible DB format. The tree extraction toolkit can extract the following geometry attributes: the height of the tree, the diameter of the trunk, the crown diameter and the trunk and crown offset from the tree location. The user can specify other attributes for each tree, like last checkup date, tree species, placement type, etc. The stored attributes are entirely up to the users, there is a pre-defined template inside PCS for this type of work, but the user can expand it with his/her attributes. We strongly recommend using the Append Tree Attributes to have the proper attribute structure for the software.
The toolkit works with any type of point cloud as the semi-automation is rule-based, which means it inspects geometry and intensity. Weaker clouds tend to work worse than stronger clouds. Some clouds are not appropriate for the 1-click solution, in that case, we recommend the 5-click solution (which might be faster than the 1-click in some cases). TLS datasets tend to be “slower” while using the toolkit due to the higher point density.
The first step to establishing the database is to open the point clouds and set the display according to the needs. In our example, we are using a parking lot with intensity colouring. It is recommended to use the colourizer setting to modify the intensity ranges from the reddish range to the blueish range.
When the point cloud is loaded, the user can load the clouds to 3D view using the 3-point clip frame tool, and reload the 3D view.
It is highly recommended to load the trees - which the user wishes to extract - to the 3D view for better visual feedback, even if the tool itself is capable of operating based on the 2D view. After the cloud is ready, the user can open an existing SHP or FDB for the extraction or create an empty point SHP and append the attributes. We mainly focus on extracting into SHP files, but the process is nearly identical with FDB files.
Create an empty point SHP, set it active, and start to modify the attribute table structure.
To append the required attributes, use the Append Tree Attributes function from the Complex Measures toolbar. The software will automatically append the required numerical attributes to the SHP file.
Append further attributes if needed. For numeric attributes, it is always recommended to use 2 decimals, but if the user requires only whole meters, the decimals can be set to 0, and the software will store only whole meters. For string attributes, we always recommend specifying longer lengths than needed. For advanced use cases, the users can also use the lookup editor to pre-define values to a dropdown list.
After the attributes are set, the extraction can be started. It is however recommended to prepare templates for the text attributes to avoid manual data entry, if possible. In our example, we created a Coniferous and a Deciduous template, where only the t_class attribute is pre-set. The inactive fields will not be affected by the template.
Before starting the extraction tool, select the appropriate template from the template list on the left side of the attribute table.
The user can utilise the 1-point or the 5-point tree measurement tools from the Complex Measures Toolbar.
After the tree is selected with 1 or 5 points, the extraction window displays the tree and the parameters.
Using the extraction panel the user can adjust the dimensions in the two section views or adjusting the values on the right. Different view options support the user to adjust the section view as well. The user can select an attribute value for the Field of Height (tree height), Field of Diameter (trunk diameter) and Field of Crown diameter from the dropdown menu. Please note that the used attributes (trunk_h, trunk_d, and crown_d) are automatically assigned by the tool if properly named. The further settings are explained in the Complex Measures Toolbar article.
After everything is set, press Accept. The tool will store the tree, the point will appear at the appropriate location, and the user can select another tree. Repeat the process as many times as needed. In our example, the attribute table is docked to the bottom part of the main window, so the user can see all attributes. If needed, adjust the values manually.
If needed, the user can generate crown and trunk polylines based on the stored attributes for better visualisation.
The SHP file can be used in other GIS systems, like ArcGIS Pro or QGIS in various other use cases. When a tree inventory is built, the SHP format is perfect for delivering the client, as all attributes are there and every GIS software can handle the files.
In case the tree inventory shall be delivered to the client in CAD format, we strongly recommend reading the Extraction for CAD environments article and applying the described principles. In a nutshell, the following steps shall be taken:
Please note that the software can export in KML, CSV or Geojson format as well, if the data shall be delivered in another format.