Rasters are spatial continuous distributions of geospatial data. We have been shown that we an work with data in raster format using either raster and working on object directly, or via dplyr and using the normal data manipulation routines that we’ve learned for non-spatial data. In this in class exercise, you may use both of these techniques to load, manipulate, and display geospatial data.

The Raw Data

The data for this will be the same Baja California data we showed in the lectures on points and rasters.

raster_url <- "https://github.com/dyerlab/ENVS-Lectures/raw/master/data/alt_22.tif"
beetle_url <- "https://raw.githubusercontent.com/dyerlab/ENVS-Lectures/master/data/Araptus_Disperal_Bias.csv"

The Questions

  1. Load the raster and point data in and crop to an appropriate size to display the locations of the sampling plots and make a label for each site.

  2. Use the click() function to crop the raster and filter the sites to include only the region that is on the peninsula of Baja California. Plot the raster and sites as labels.

  3. The peninsula of Baja California is divided into the States of Baja California Norte and Baja California Sur. The border between these states is at 28° Latitude. Divide the sample locations into groups based upon which state they are located and plot the average sex ratio of the sample sites partitioned by each site.

  4. Is there a relationship between the observed sex ratio and the elevation at that site?

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