Applications in GIS - M2 Forestry and LiDAR

 

LiDAR imagery of the Big Meadows Area in the Shenandoah National Park, VA. This three dimensional view is through using a Scene as the basemap in ArcPro.

In week 2 of Applications in GIS we looked at LiDAR imagery and used a series of tools within ArcPro Spatial Analyst and ArcPro 3D Analyst programs to digest the data into maps that displayed elevation, vegetation cover, vegetation height, and tree canopy density. This module was an exercise in manipulating three-dimensional data into different feature types, including points and rasters, and helped emphasize the myriad of information that can be gained from a good LiDAR .las file.

 One of the first tasks in our lab after downloading and extracting the las file into ArcPro was to create a basic digital elevation model (DEM) by filtering to display only ground points and generating a raster using the LAS Dataset to Raster tool. For this tool we used natural neighbor to fill voids and a sampling value of 6 with cell size as the sampling type. Our second task was to create a digital surface model (DSM) by filtering only the non-ground points and using the tool to create a raster again with the same settings. The result of this left us with two comparable rasters, one displaying ground topography and another displaying points that were non-ground topography (ostensibly, trees). 

With these two rasters we used the Minus tool to get the difference between 'tree surface elevation' (DSM) and the 'ground elevation' (DEM) which left us with tree height over the area. 

Full-console view of the digital surface model (DSM) derived from the LiDAR data; a raster displaying the elevation on non-ground points in the .las file.  

The next objective was to calculate vegetation biomass density, but first we needed to change the .las 3D shape into multipoint datasets again distinguishing the ground from vegetation. This was accomplished by running the LAS to Multipoint tool with average point spacing from the .las file, and Class Code as 2 for the ground and 1 for the vegetation. [These class codes are determined from the .las metadata]. We converted the multipoint files with Point to Raster, and set the cell size to 3 times the point spacing of the .las file. Basic data cleanup with the IS NULL and Con tools helped fill in empty values in the rasters. Then we used the Plus, Float, and Divide tools to calculate a raster that contained the tree canopy density based on the number of vegetation points and ground points in the cell. 

Final objectives from this lab; a calculated raster displaying canopy density and another displaying canopy height, here represented with a histogram. Both of these could be valuable tools for forestry management.

These products were both fairly quick calculations in ArcPro from the LiDAR data to determine tree height and canopy density through the surveyed area, and they clearly displayed areas with human structures, healthy forest, and disturbed or sparse areas. These maps would be highly useful to a land manager or forester since they quickly highlight the vegetation resources in a consistent manner throughout the survey area.