Harvard Forest Soils Analysis (NEON)

The National Ecological Observatory Network has invested in high-resolution airborne imaging of their field sites. Elevation models generated from LiDAR can be used to map the topography and vegetation structure at the sites.

Check to see if there is a data directory in your workspace with harv subdirectory in it. If not, Download the data and extract it into your working directory. The harv directory contains spatial data for Harvard Forest including raster data for a digital terrain model (harv_dtmfull.tif) and a digital surface model (harv_dsmfull.tif), and polygon data for the site boundary (harv_boundary.shp) and the soil types (harv_soils.shp).

1. Make a map of the harv_soils data with the polygons colored based on DRAINAGE_C column. Use the viridis color ramp.
2. Make a map of the harv_soils data with one facet (i.e., subplot) for each category in the DRAINAGE_C column.
3. Using the harv_dtmfull.tif and have_dsmfull.tif rasters create a canopy height model (DSM - DTM) and extract the maximum canopy height (i.e., the CHM value) within each soils polygon. To get the maximum canopy height instead of the mean value use the max function instead of mean. Display a vector of the resulting canopy height.
4. Add the vector of canopy heights from (3) to the original sf object and display the resulting data frame.
5. Make a map of the soil polygons colored based on their maximum canopy height. Use the viridis color ramp.
6. Make a map that is the same as (5), but preserves the UTM coordinates on the axes.

Expected outputs for Harvard Forest Soils Analysis