Merge pull request #1101 from datacarpentry/spatial-update

Add buffer to canopy height from space

Author: ethanwhite

exercises/Neon-canopy-height-from-space-R.md

@@ -21,4 +21,5 @@ The `SJER` directory contains raster data for a digital terrain model (`sjer_dtm
 7. Create a map that shows the `SJER` boundary and the plot locations colored by the canopy height values.
 8. Create a map that shows the canopy height model raster, but in `cm` rather than `m` (i.e., multiply the canopy height model by 100).
 9. Create a map that shows the digital terrain model raster, the plot locations, and the `SJER` boundary, using transparency as needed to allow all three layers to be seen. Remember all three layers will need to have the same CRS.
-10. Conduct an analysis of the relationship between elevation and canopy height at the SJER plots. Start by extracting the mean elevations (i.e., the values from the digital terrain model) at each plot location for `SJER` and adding them to the spatial plots data so that this data now includes both the elevations and the canopy heights. Then make a scatter plot showing the relationship between elevation and canopy height using this data. Color the points by `plot_type` and fit a linear model through all of the points together (not separately by `plot_type`). Finally, use `dplyr` to calculate the average canopy height and average elevation for the two different plot types. Give the axes good labels.
+10. Conduct an analysis of the relationship between elevation and canopy height at the SJER plots. Using a 50m buffter, extract the mean elevations (i.e., the values from the digital terrain model) and the canopy heights at each plot location for `SJER` and add to the spatial plots data to produce a simple features object that includes both the average elevations (in a 50 m buffer) and the canopy heights (in a 50 m buffer). Then make a scatter plot showing the relationship between elevation and canopy height using this data.
+Color the points by plot type and fit a single smooth curve through all of the points. Finally, use `dplyr` to calculate the average canopy height and average elevation for the two different plot types.