Methods:

The canopy dataset is derived from LiDAR (Light Detection and Ranging) data captured by Aerometrex and the ACT Government (available here) at 12ppm over the ACT and region in April 2020. Tree crowns were delineated using a one metre 2020 LiDAR Canopy Height Model (CHM) via a marker-controlled watershed delineation method (Popescu & Wynn 2004; Plowright & Roussel 2020). A 3X3 low pass smoothing algorithm was applied to the CHM raster. The CHM was then loaded into R and manipulated using the ForestTools R-package (Plowright & Roussel 2020). A variable window filter, which was used in parallel with watershed segmentation, was applied to determine locations of treetops. This algorithm employs a moving window for the CHM to filter pixels, the highest value within the window is regarded as a treetop. The size of the moving window differs and depends on the positive relationship between crown width and tree height. The following metrics was used for the variable window:function(x){((x^2)* 0.009 + 2.5)}. A minimum height of 3 metres was set for the treetop detection algorithm. The resulting dataset, which contained attributes for unique tree identifiers, tree height and moving window size, was saved as a point shapefile. The watershed segmentation method was implemented within the ForestTools R-package to outline tree crowns, using the previously identified treetops as markers. The resulting segmented raster was converted to a simplified polygon layer, and joined with the treetops point layer. Polygons smaller than 3 square metres were removed. Tree crown polygons larger than 100m2 and higher than 8 metres were filtered as "mature trees". Dataset represents native and non-native species.

Also see 

References:

Plowright, A & J Roussel. ForestTools: Analyzing Remotely Sensed Forest Data. R Package Version 0.2.4. 2021. https://cran.r-project.org/web/packages/ForestTools/index.htmlPopescu SC & Wynne RH 2004. Seeing the Trees in the Forest: Using Lidar and Multispectral Data Fusion with Local Filtering and Variable Window Size for Estimating Tree Height. Photogrammetric Engineering & Remote Sensing Vol. 70, No. 5, pp. 589–604.