Data Carpentry for Pharmacists
Teaching the tools to get computers to do cool science
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.
This data gets really powerful when you can compare ecological processes across
sites.
Download the elevation models for the Harvard Forest (HARV) and San Joaquin Experimental Range (SJER)
and the plot locations for each of these sites.
Often, plots within a site are used as representative samples of the larger site
and act as reference areas to obtain more detailed information and ensure
accuracy of satellite imagery (i.e., ground truth).
Generate a Canopy Height Model for each site (HARV and SJER) using simple raster math, where chm = dsm - dtm.
plot() the chm and hist() of canopy heights for each site on a single
panel. The raster package modifies plot() from the basic R graphics
package, so use par(mfrow=c(2,2), mar=c(5, 4, 2, 2)) prior to plotting to get
the four figures on the same panel and to set margins to make labels visible.
Add the plot_locations to the site images. Use the add=TRUE argument in another plot() immediately proceeding plotting the site image to add the plot points.
Don’t see the plot_locations on the map??? Compare the crs(chm) to
crs(plot_locations). HINT: They should be the same.
Extract the maximum canopy heights for each plot at both sites within 10 meters of the center of the plot.
