Scottish Munros

geography
maps
Mountains in Scotland
Author

Cole Baril

Published

August 19, 2025

Load Packages

require(pacman)
p_load(tidytuesdayR, magick, trashpanda, tidyverse, janitor, tidytext, slider, here, TTR, sf, rnaturalearth, rnaturalearthdata, patchwork)

Load Data

tuesdata <- tidytuesdayR::tt_load('2025-08-19')
scottish_munros <- tuesdata$scottish_munros

Plot

# Get UK countries (scotland, england, etc.) from Natural Earth
uk <- ne_countries(country = "United Kingdom", scale = "medium", returnclass = "sf")

# Transform UK shapefile to British National Grid
uk_bng <- st_transform(uk, crs = 27700)


# Get rivers and lakes
rivers <- ne_download(scale = "medium", type = "rivers_lake_centerlines", category = "physical", returnclass = "sf")
lakes <- ne_download(scale = "medium", type = "lakes", category = "physical", returnclass = "sf")
rivers_bng <- st_transform(rivers, crs = 27700)
lakes_bng <- st_transform(lakes, crs = 27700)

# Get major cities
cities <- ne_download(scale = "medium", type = "populated_places", category = "cultural", returnclass = "sf")
cities_bng <- st_transform(cities, crs = 27700)

# Make sf object with British National Grid CRS
df_sf <- st_as_sf(scottish_munros |> drop_na(xcoord, ycoord), coords = c("xcoord", "ycoord"), crs = 27700)

density <- ggplot() +
  geom_sf(data = lakes_bng, fill = "lightblue", color = NA) +
  geom_sf(data = rivers_bng, color = "blue", size = 0.5) +
  geom_sf(data = uk_bng, fill = NA, color = "black", size = 0.7) +
  stat_density_2d(
    data = df_sf,
    aes(x = st_coordinates(df_sf)[,1], y = st_coordinates(df_sf)[,2], fill = after_stat(level * 1e9)),
    geom = "polygon",
    alpha = 0.4,
    color = NA,
    h = c(40000, 40000)
  ) +
  scale_fill_viridis_c(option = "magma", name = "2D Kernel Density (x1e9)") +
  coord_sf(crs = 27700,
           xlim = c(0, 470000),
           ylim = c(530000, 1200000)) +
  theme_void() +
  theme(
    panel.border = element_rect(color = "black", fill = NA, size = 1),
    panel.background = element_rect(fill = "white"),
    legend.position = "bottom",
    legend.title = element_text(vjust = 0.5, size = 25, margin = margin(r = 8)),
  ) 


points <- ggplot() +
  geom_sf(data = lakes_bng, fill = "lightblue", color = NA) +
  geom_sf(data = rivers_bng, color = "blue", size = 0.5) +
  geom_sf(data = uk_bng, fill = NA, color = "black", size = 0.7) +
  scale_fill_viridis_c(option = "magma", name = "Density") +
  geom_sf(
    data = df_sf,
    aes(color = Height_m, size = Height_m),
    alpha = 0.8) +
  scale_color_viridis_c(option = "plasma", name = "Height (m)", label = add_commas) +
  scale_size_continuous(range = c(1,5), guide = "none") +
  coord_sf(crs = 27700,
           xlim = c(0, 470000),
           ylim = c(530000, 1200000)) +
  theme_void() +
  theme(
    panel.border = element_rect(color = "black", fill = NA, size = 1),
    panel.background = element_rect(fill = "white"),
    legend.position = "bottom",
    legend.title = element_text(vjust = 0.5, size = 25, margin = margin(r = 20))) 

plot <- points + density +
  plot_annotation(
    title = "Scottish Munros",
    subtitle = "Scottish Munros are largely clustered around three central points"
  ) &
  theme(legend.key.width = unit(2, "cm"),
        legend.key.size = unit(1.5, "lines"),
        legend.text = element_text(size = 20),
        plot.title = element_text(face = "bold", hjust = 0.5, size = 40),
        plot.subtitle = element_text(hjust = 0.5, size = 30))


# Save and display images
current_dir <- dirname(knitr::current_input())
plot_name <- "scottish_munros.png"

ggsave(plot = plot, 
       dpi = "screen",
       width = 22,
       height = 20,
       device = ragg::agg_png,
       filename = file.path(current_dir, plot_name))


# Read the big plot
img <- image_read(file.path(current_dir, plot_name)) 


# Force 16:9 aspect ratio with minimal padding
# Target size: 1200x675 px (16:9)
img_card <- image_scale(img, "1200x675")           # scale to fit inside 16:9
img_card <- image_extent(
  img_card,
  geometry = "1200x675",
  gravity = "center"
)

# Save as card preview
image_write(img_card, path = file.path(current_dir, "preview.png"))

knitr::include_graphics(
  file.path(current_dir, plot_name)
)

References

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