M2

 

In this project, I created several raster maps from a LiDAR dataset to analyze forest structure and biomass. First, I generated a Digital Elevation Model (DEM) and a Digital Surface Model (DSM) by filtering the LAS dataset to isolate ground and non-ground points, respectively. Using these rasters, I calculated a Height raster to estimate tree heights by subtracting the DEM from the DSM. Then, I created a Canopy Density raster to assess vegetation density by comparing vegetation and ground return counts. One of the main challenges I ran into was locating the “Filters” option for the LAS dataset. Initially, I didn’t see it in the Contents pane and struggled to isolate ground points. I eventually realized that I needed to use a LAS Dataset (.lasd) file and switch to the Appearance tab in the 3D Scene view to access point classification filters like Ground or Vegetation. Once that was resolved, I was able to proceed with creating the DEM and DSM accurately. Another minor issue was understanding how to extract meaningful values from the height raster. I had to use the Identify tool and Raster Calculator to locate cells with negative values or heights over 196 feet, and I learned that some negative values were due to return errors near roads or edges. Despite these challenges, the final maps provided useful insights into tree height distribution and canopy density across the landscape.