Global Border Crossings

Geographically Mapping the International Border Crossings, colour coded by their infrastructure development.

Michael R. Kenwick and colleagues have compiled the Border Crossings of the World dataset, which examines how state authority is manifested through infrastructure at international borders. Using satellite imagery, the researchers identified the presence of gates, official structures, and split-lane inspection facilities. Their dataset finally computes a overall summary metric called “border orientation score” (measured at the directed border crossing year) that assesses the degree to which a state demonstrates its commitment to controlling the terms of border penetration through spatial displays of its capacities. This information was brought to light by Erik Gahner and Data is Plural (April 17, 2024 Edition) | Data Codebook | Data

Comparison of Infrastructure at the Border Crossings. West-European and West-African border crossings are the least secured, while Eastern Europe and US-Mexico Border have high checking infrastructure.

How I made this graphic?

Load libraries and Data, Creating custom functions

# Data Wrangling Tools
library(tidyverse)
library(janitor)
library(here)
library(dataverse)

# Final plot tools
library(scales)
library(fontawesome)
library(ggtext)
library(showtext)
library(colorspace)
library(ggthemes)
library(patchwork)

# Mapping tools
library(rnaturalearth)
library(sf)
library(patchwork)

# Data Load-in, EDA & Data Wrangling 

border <- get_dataframe_by_id(
  fileid = 4556046,
  .f = readr::read_tsv,
  server = "dataverse.harvard.edu"
) |> 
  as_tibble()

# Create a function to draw a bounding box to plot a rectangle on Map
geometric_rectangle <- function(lat_min, lat_max, lon_min, lon_max) {
  box_coords <- matrix(
    data = c(
      c(lon_min, lon_max, lon_max, lon_min, lon_min),
      c(lat_min, lat_min, lat_max, lat_max, lat_min)
    ),
    ncol = 2, byrow = FALSE
  )
  return(
    st_polygon(list(box_coords)) |> 
      st_sfc(crs = 4326)   # Set the CRS to EPSG:4326, the default
  )
} 

Visualization Parameters

# Font for titles
font_add_google("Scope One",
  family = "title_font"
) 

# Font for the caption
font_add_google("Saira Extra Condensed",
  family = "caption_font"
) 

# Font for plot text
font_add_google("Barlow Semi Condensed",
  family = "body_font"
) 

showtext_auto()

bg_col <- "lightblue" # Background Colour
text_col <- "grey15" # Colour for the text
text_hil <- "grey20" # Colour for highlighted text

# Define Text Size
ts <- 40 # Text Size

# Caption stuff
sysfonts::font_add(
  family = "Font Awesome 6 Brands",
  regular = here::here("docs", "Font Awesome 6 Brands-Regular-400.otf")
)
github <- "&#xf09b"
github_username <- "aditya-dahiya"
xtwitter <- "&#xe61b"
xtwitter_username <- "@adityadahiyaias"
social_caption_1 <- glue::glue("<span style='font-family:\"Font Awesome 6 Brands\";'>{github};</span> <span style='color: {text_hil}'>{github_username}  </span>")
social_caption_2 <- glue::glue("<span style='font-family:\"Font Awesome 6 Brands\";'>{xtwitter};</span> <span style='color: {text_hil}'>{xtwitter_username}</span>")

Plot Text

plot_title <- "International Border Crossings"
plot_caption <- paste0(
  "**Data:** Border Crossings of the World by Michael R. Kenwick et al", 
  " |  **Code:** ", 
  social_caption_1, 
  " |  **Graphics:** ", 
  social_caption_2
  )
subtitle_text <- "Comparison of Infrastructure at the Border Crossings. West-European and West-African border crossings are the least secured, while Eastern Europe and US-Mexico Border have high checking infrastructure."
plot_subtitle <- str_wrap(subtitle_text, width = 105)
plot_subtitle |> str_view()

Data Analysis and Wrangling

# Data on Border Crossings - Selected Fields to plot on the World Map
plotdf <- border |> 
  dplyr::select(borderid, country1, country2, 
         lat, long,
         theta, visa_waiver) |> 
  group_by(borderid) |> 
  summarise(
    lat = mean(lat), lon = mean(long),
    theta = mean(theta),
    visa_waiver = mean(visa_waiver)
  ) |> 
  st_as_sf(coords = c("lon", "lat"), crs = 4326)

# Getting a World Map for Base Plot
world <- ne_countries(
  scale = "large",
  type = "countries",
  returnclass = "sf"
)

# Adding the politically correct map of India to the World Map by ne_countries()
india_correct <- read_sf(here("data", "india_map", "India_State_Boundary.shp")) |> 
  st_simplify(dTolerance = 500) |> 
  rmapshaper::ms_dissolve() |>            # removing the internal state borders
  rmapshaper::ms_simplify(keep = 0.2)     # removing left over multiploygons

The Base Plot - World Map

g_base <- ggplot() +
  geom_sf(
    data = world,
    fill = "white",
    colour = text_col,
    linewidth = 0.05
  ) +
  geom_sf(
    data = india_correct,
    fill = "white",
    colour = text_col,
    linewidth = 0.05
  ) +
  geom_sf(
    data = plotdf,
    mapping = aes(
      colour = theta
    ),
    alpha = 0.75,
    shape = 1,
    size = 2,
    stroke = 0.5
  ) +
  geom_sf(
    data = geometric_rectangle(35, 70, -10, 40),
    fill = NA, colour = text_col,
    linewidth = 0.3, 
    linetype = 3
  ) +
  coord_sf(
    crs = this_crs,
    expand = FALSE
  ) +
  paletteer::scale_colour_paletteer_c(
    "grDevices::Temps",
    breaks = seq(-2, 2, 1),
    limits = c(-2, +2),
    oob = scales::squish,
    labels = c(
      "Minimal",
      "Less",
      "Average",
      "More",
      "Most developed"
    ),
    name = "Infrastructure at the Border Crossing",
    na.value = "#EAD68EFF"  # Impute average value to missing values
    ) +
  labs(
    title = plot_title,
    subtitle = plot_subtitle, 
    caption = plot_caption
  ) +
  ggthemes::theme_map(
    base_family = "body_font",
    base_size = ts
  ) +
  theme(
    plot.background = element_rect(
      fill = bg_col,
      linewidth = NA, 
      colour = NA
    ),
    legend.position.inside = c(0.4, 0.1),
    legend.justification = c(0, 0),
    legend.direction = "horizontal",
    legend.title.position = "top",
    legend.key.width = unit(15, "mm"),
    legend.key.height = unit(3, "mm"),
    legend.title = element_text(
      hjust = 0.5, 
      margin = margin(0,0,2,0,"mm"),
      face = "bold",
      colour = text_col,
      size = 1.2 * ts
    ),
    legend.text = element_text(
      margin = margin(1,0,0,0, "mm"),
      size = 0.75 * ts,
      family = "caption_font"
    ),
    legend.background = element_rect(fill = NA, colour = NA),
    plot.title = element_text(
      size = ts * 4,
      colour = text_hil,
      family = "title_font",
      margin = margin(10,0,1,0,"mm"),
      hjust = 0.5
    ),
    plot.subtitle = element_text(
      hjust = 0.5, 
      lineheight = 0.3,
      colour = text_col,
      family = "caption_font",
      margin = margin(0,0,2,0,"mm"),
      size = 1.5 * ts
    ),
    plot.caption = element_textbox(
      hjust = 0.5,
      family = "caption_font",
      colour = text_hil,
      margin = margin(0,0,5,0,"mm")
    ),
    plot.margin = margin(0,0,0,0, "mm")
  )

Add-on maps, insets and annotations

# Define limits of the inset map
map_lim <- geometric_rectangle(36, 70, -10, 38) |> 
  st_transform(this_crs) |> 
  st_bbox()

# A subtitle for the inset
inset_subtitle <- "Those is <b style='color:#089392FF'> Western Europe </b> have minimal infrastructure,<br>perhaps due to free movement in the Schengen Area.<br> In contrast, <b style='color:#CF597EFF'> East-Europe  </b> have checks & high infrastructure,<br>perhaps a reminiscent of the 'Iron Curtain'!"
inset_title <- "Europe's border crossings"

set.seed(42)
g1 <- ggplot() +
  geom_sf(
    data = world,
    fill = "white",
    colour = "black",
    linewidth = 0.1
  ) +
  geom_sf(
    data = plotdf,
    mapping = aes(
      colour = theta
    ),
    alpha = 0.75,
    shape = 1,
    size = 1,
    stroke = 1.2
  ) +
  geom_sf_text(
    data = world,
    aes(label = sovereignt),
    family = "caption_font",
    colour = text_hil,
    size = ts/7
  ) +
  coord_sf(
    xlim = c(map_lim["xmin"], map_lim["xmax"]),
    ylim = c(map_lim["ymin"], map_lim["ymax"]),
    expand = FALSE,
    crs = this_crs
  ) +
  paletteer::scale_colour_paletteer_c(
    "grDevices::Temps",
    breaks = seq(-2, 2, 1),
    limits = c(-2, +2),
    na.value = "#EAD68EFF",
    oob = scales::squish
    ) +
  labs(
    subtitle = inset_subtitle,
    title = inset_title
  ) +
  ggthemes::theme_map(
    base_size = 0.5 * ts,
    base_family = "body_font"
  ) +
  theme(
    plot.subtitle = element_markdown(
      lineheight = 0.3,
      margin = margin(0.5,0,1,0, "mm"),
      colour = text_col
    ),
    plot.title = element_text(
      margin = margin(0,0,0,0, "mm"),
      colour = text_col,
      face = "bold"
    ),
    panel.border = element_rect(
      fill = NA,
      linewidth = 0.5,
      linetype = 3,
      colour = text_col
    ),
    legend.position = "none"  
    )

# QR Code for the plot
url_graphics <- paste0(
  "https://aditya-dahiya.github.io/projects_presentations/data_vizs/",
  
  # The file name of the current .qmd file
  "border_crossings",           # Add the name of the file here
  
  
  ".html"
)
# remotes::install_github('coolbutuseless/ggqr')
# library(ggqr)
plot_qr <- ggplot(
  data = NULL, 
  aes(x = 0, y = 0, label = url_graphics)
  ) + 
  ggqr::geom_qr(
    colour = text_col, fill = bg_col
    ) +
  coord_fixed() +
  theme_void() +
  theme(plot.background = element_rect(
    fill = NA, 
    colour = text_col,
    linewidth = 1,
    linetype = 1
    )
  )

Compiling Plots with Patchwork

g <- g_base +
  
  # Add inset to the plot
  inset_element(
    p = g1, 
    left = 0, right = 0.27,
    top = 0.65, bottom = 0.01,
    align_to = "plot"
  ) +
  
  # Add QR Code
  inset_element(
    p = plot_qr,
    left = 0.9, right = 1,
    top = 0.3, bottom = -0.1,
    align_to = "plot"
  ) +
  plot_annotation(
    theme = theme(
      plot.background = element_rect(
        fill = bg_col, 
        colour = NA, linewidth = 0
      )
    )
  )

Savings the graphics

ggsave(
  filename = here::here("data_vizs", "border_crossings.png"),
  plot = g,
  width = 297,    # Default A4 size page
  height = 210,   # Default A4 size page
  units = "mm",
  bg = bg_col
)


library(magick)
# Saving a thumbnail for the webpage
image_read(here::here("data_vizs", "border_crossings.png")) |> 
  image_resize(geometry = "400") |> 
  image_write(here::here("data_vizs", "thumbnails", "border_crossings.png"))