The Tree Canopy tool provides you with three different methods for Canopy cover analysis:
Canopy Coverage
Canopy Coverage is the percentage area of each raster cell that is covered by tree canopy. Simple statistics on an area will tell you what the total percentage and area of tree canopy coverage is. It could also be used as a measurement of the percentage of a cell that receives direct sunlight.
Canopy Density
Tree Canopy Density is a proxy measure of the thickness of the tree canopy within the area of a raster cell. The measurement of how difficult it is for the LiDAR Laser shots to penetrate through the canopy to the ground is a proxy for the canopy density. Each raster cell will be populated with a value from 0 to 1, representing the density of the canopy over the area of that cell.
The above methods work by counting both ground classified and vegetation classified returns that are within each raster cell (or within a defined radius of the center of each cell) and returning the ratio of vegetation returns to the total number of ground and vegetation returns. They differ in the filtering rules that are used to select the returns from the LiDAR survey for processing.
Canopy Height
The Canopy Height method uses classified LiDAR survey data to generate raster output of the height of the tree canopy across the survey area.
Input Filtering
LiDAR Classification
The spatial location of each return, the “Classification” and the “Z” data are used in the processing. If you have version 1.4 LAS files (or later), you can elect to use the “Extended Classification” data in preference. If your LiDAR data has not been classified, then it will not be suitable for use in this tool. As a minimum requirement, the data must have either ground returns or vegetation returns appropriately classified.
You must provide a list of classification codes, which can be either industry-standard codes or extended codes of your choice, for everything that represents “Ground” and everything that you consider represents “Vegetation”. The best quality result will be obtained if you provide a list of codes for both ground and vegetation. For example, you might supply “Ground” and “Water” as ground classifications and “High vegetation” as the vegetation classification.
If you have both ground and vegetation classified returns, then use the “Ground and Vegetation” mode to allow you to enter lists of both. If you only have ground returns classified, then you can use the “Ground and Not Ground” mode. If you only have vegetation returns classified, then you can use the “Not Vegetation and Vegetation” mode.
Integration Area
The number of returns must be integrated over some areas. By default, we do this over the area of a single raster cell. In this scenario, you ought to choose a cell size that is large enough to ensure that there are a sufficient number of hits in each cell to provide statistical significance. This produces the highest resolution result, which is likely to be best for statistical analysis but can be quite variable and difficult to visualize.
Output raster
The tool will create an output raster containing a floating point band in MRR format. The band will record the Tree Canopy Height above ground.
You can also populate cells that contain no processed LiDAR vegetation returns with zero. Otherwise, these raster cells will be empty by default. If you populate these empty cells, you will usually use some clipping rectangle or clipping polygon to restrict the spatial extent of the output raster.