Homework 4

sf Maps; Animation Plots

Author

Byeong-Hak Choe

Published

April 23, 2025

Modified

April 23, 2025

Direction

  • Please submit your R script for Homework 4 to Brightspace with the name below:

    • danl-310-hw4-LASTNAME-FIRSTNAME.R
      ( e.g., danl-310-hw4-choe-byeonghak.R )

  • The due is May 5, 2025, 2:00 P.M.

  • Please send Byeong-Hak an email (bchoe@geneseo.edu) if you have any questions.




Part 1. ggmap visualization

Question 1

Replicate the following map using Classwork 10 example.

  • Below Google font families are used:

    • Title and Label: Pacifico
    • Subtitle and Legend: Annie Use Your Telescope
    • Caption: Alegreya Sans

  • scale_*_colorblind() is used to make a plot colorblind-friendly.

  • The following option is used to create the figure.

ggsave("PATHNAME_OF_GGPLOT_OUTPUT.png",
       plot = p, height = 12, width = 8, units = "in")



Part 2. Simple Feature (sf) and Aninimation Plots

Consider the county-level climate opinion data from Yale Program on Climate Change Communication:

climate_opinion <- read_csv(
  'https://bcdanl.github.io/data/climate-change-public-opinion.csv')


Question 2

  • Replicate the following map about variable human:
    • human: Estimated percentage who think that global warming is caused mostly by human activities


  • For R packages and map data, use the following:
# Load required packages ---------------------------------------------------
library(tidyverse)   
library(sf)          # simple-features objects for spatial data
library(tigris)      # fast access to Census TIGER/Line shapefiles
library(ggthemes)    
library(gganimate)   # turn static ggplots into animations
library(showtext)    # Google-font rendering inside R graphics

# Register Google fonts so they render the same on any machine -------------
font_add_google("Roboto",       "roboto")  # body text
font_add_google("Alegreya Sans","aleg")    # title text
showtext_auto()                            # activate showtext globally

# 1) Download   US state & county geometries (simplified “cartographic” 
#    boundaries) at 1:5 million scale, then shift Alaska, Hawai‘i & PR closer ---

us_states <- states(
  cb         = TRUE,   # use generalized cartographic boundary files
  resolution = "5m",   # 1 : 5 000 000
  year       = 2024    # 2024 vintage
) |> 
  shift_geometry()     # moves AK/HI & PR into a CONUS-friendly layout

us_counties <- counties(
  state      = NULL,   # all states + DC + territories
  cb         = TRUE,
  resolution = "5m",
  year       = 2024
) |> 
  shift_geometry()

# 2) Build a bounding box that covers only the 50 states -------------------
#    (exclude DC + territories so the map crops nicely)

main_states <- states(cb = TRUE, resolution = "5m", year = 2024)

keep <- state.abb                        # built-in vec of 50 state abbr.
main_states <- main_states |>
  filter(STUSPS %in% keep) |>
  shift_geometry()

bb <- sf::st_bbox(main_states)           # xmin / ymin / xmax / ymax vector

# 3) Quick static map -------------------------------------------------------
ggplot() +
  geom_sf(data = us_counties,
          fill  = NA,        # counties as thin outlines
          color = "grey80",
          linewidth = 0.01) +
  geom_sf(data = us_states,
          fill  = NA,        # thicker state borders
          color = "black") +
  coord_sf(                   # crop to 50-state bounding box
    xlim   = c(bb["xmin"], bb["xmax"]),
    ylim   = c(bb["ymin"], bb["ymax"]),
    expand = FALSE
  ) +
  theme_map()                 # clean, border-free background



Question 3

  • Animate the maps for the even-numbered years used in Question 2:

  • For animate(), use the following parameter setting:
ggplot() +
  ...
 labs(subtitle = "Year: {floor(frame_time)}") +
  ...

anim <- animate(p_anim, 
                nframes = 20, 
                fps = 5, 
                width = 8, height = 5,
                units = "in",
                res = 900)  # resolution can be reduced

# To save animation as PATHNAME_FOR_YOUR_FILE.gif
anim_save("PATHNAME_FOR_YOUR_FILE.gif", anim)

  • You can open “PATHNAME_FOR_YOUR_FILE.gif” in any web browser.

  • transition_time(year) treats year as a continuous numeric variable.

  • After you call animate(), gganimate:

  1. Spans the full numeric range of the variable — here 2014 → 2024, a width of 10 years.
  2. Slices that span into nframes equally spaced instants.
    • Here nframes = 20, so the frame-to-frame step is \[ \begin{align} \Delta = \frac{2024 - 2014}{20 - 1} \;=\; \frac{10}{19} \;\approx\; 0.526 \text{ years}. \end{align} \]
  3. Assigns each frame its own “virtual” time stamp:
    • \(t_0 = 2014\), \(t_1 = 2014.526\), \(t_2 = 2015.053\), …
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