Week 2: Discussion Section

Working with multiple vector types

Author

Alessandra Vidal Meza

Published

May 13, 2025

1. Learning Objectives

  • Use sf::st_read() to read multiple vector data types
  • Retreive the CRS of a vector object with sf::st_crs()
  • Transform CRS and match across all vector data types with sf::st_transform()
  • Perform dplyr attribute manipulations (e.g. filter(), mutate(), select())
More map making in R

There are MANY different ways to make maps in R, all with different pros/cons. Check out this resource for examples of what map making looks like in ggplot2, leaflet, and more!

2. Get Started

  • Create an .Rproj as your version controlled project for Week 2
  • Create a Quarto document inside your .Rproj
  • Download this folder from Google Drive and move it inside your .Rproj
  • Load all necessary packages
library(here)
library(tidyverse)
library(sf)
library(tmap)

3. Your Task

You will be wokring with the following datasets:

Now, to meet this week’s learning objectives, your task:

  1. Read in the data for Colombia’s ecoregions, roads, and bird observations
  • Use st_read() to read vector data (e.g., .shp, .gdb)
  • Use rename() or mutate() to rename the columns decimal_longitude and decimal_latitude to long and lat in aves and sf::st_as_sf() to convert it into an sf object
    • Hint: To convert a table into a vector object, you can use st_as_sf() but remember to check the class() of an object first!
  1. Check class() of all vector objects (including the converted aves) and use sf::st_geometry_type() to check the geometry type
  2. Use filter() to select a macro region of interest from N1_MacroBi in Colombia’s ecoregions dataset and save as a new vector data
  • Check class() of the new vector data
  • Plot the new vector data using tmap
  1. Use st_crs() to retrieve CRS of all vector objects and assign a new CRS
  • Bonus Challenge: Check units of your object with st_crs()$units
  • Check CRS of all vector objects with st_crs()
  • st_crs() <- NA is a brute force way to remove a CRS, instead:
    • For the bird observations dataset, extract the longitude and latitude from the geometry column and use sf::st_drop_geometry()
    • Convert long and lat into a geometry again with st_as_sf() to obtain a proper sf data frame
  1. Let’s bring all vector data types together
  • Check that the CRS of the ecoregions and roads datasets match
  • Transform CRS of the bird observations data using sf::st_transform() to match with the other datasets
  • Use tmap to plot the ecoregions, roads, and bird observations together