JCLambert GIS Enterprise: M2 Forestry and LiDAR

This week’s lab work involved working with a raster dataset of the Shenandoah National Park, Virginia. The data files are quite large so there were issues with loading the maps with all the finished data. We used several geoprocessing tools to produce the final map results of canopy density, digital elevation model, digital surface model, and LiDAR file. LiDAR(Light Detection and Ranging) allows for more precise information to be recorded on the Earth’s surface.

In this lab, we calculated the forest height and biomass density of the vegetation compared to the ground. Below are the tools we used in this lab.
Tools used for forest height.
*Point File Location = summarizes the contents of the LAS files, returning the minimum bounding rectangle, number of points, average point spacing, and min/max z-values.
*LAS Dataset to Raster = creates a DEM and DSM based on ground or non-ground points
*Minus = produces a tree estimation
Tools for calculating biomass density.
*LAS to MultiPoint = creates multi-point features using LiDAR files. The results are vegetation and ground. (Each tool beyond is duplicated for ground and vegetation.)
*Point to raster = Converts a raster dataset to point features.
*Is Null = Creates a binary file where 1 is assigned to all values that are not null.
*Con = Performs a conditional if/else evaluation on each of the input cells of an input raster.
*Plus = Combines sum of raster counts.
*Float = Converts each cell value of a raster into a floating point.
*Divide = Divides the values of two rasters on a cell-by-cell basis.

The initial LiDAR file required each of the aforementioned tools to be processed for canopy density. The final results of the canopy density map show the values of 0 and 1. The 0 represents the lowest density while the one represents the highest density of vegetation.

The information in the density map portrays the difference between the vegetation and ground points. This can be helpful to foresters for conservation planning in tree harvesting, terrain assessment for erosion control based on ground cover, identification and care of trees, and protecting forests as a whole. The density map aids foresters in forest maintenance more efficiently through maps. Remote sensing offers great detail through LiDAR providing foresters with more detailed maps beyond the usual topographic map.