A Roads and Highways Map of Haryana

Using Open Street Maps database to map out the roads, highways, primary, secondary and tertiary streets in Haryana State

Figure 1: Map of Haryana showing highways, roads, streets and connectivity.

How I made this graphic?

Loading libraries & data

# Data Import and Wrangling Tools
library(tidyverse)            # All things tidy
library(here)                 # File locations and paths

# Final plot tools
library(scales)               # Nice Scales for ggplot2
library(fontawesome)          # Icons display in ggplot2
library(ggtext)               # Markdown text support for ggplot2
library(showtext)             # Display fonts in ggplot2
library(colorspace)           # Lighten and Darken colours
library(patchwork)            # Combining plots

# Mapping tools
library(sf)                   # All spatial objects in R
library(osmdata)              # Getting Open Street Maps data

hy_bbox <- osmdata::getbb("Haryana")

# hy_health_docs <- opq(bbox = hy_bbox) |> 
#   add_osm_feature(
#     key = "amenity",
#     value = c("clinic", "dentist", "doctors")
#   ) |> 
#   osmdata_sf()
# 
# hy_health_hospitals <- opq(bbox = hy_bbox) |> 
#   add_osm_feature(
#     key = "amenity",
#     value = c("hospital", "nursing_home")
#   ) |> 
#   osmdata_sf()
# 
# hy_health_pharmacy <- opq(bbox = hy_bbox) |> 
#   add_osm_feature(
#     key = "amenity",
#     value = c("pharmacy")
#   ) |> 
#   osmdata_sf()
# Getting Haryana Roads and streets data
hy_roads <- opq(bbox = hy_bbox) |> 
  add_osm_feature(
    key = "highway", 
    value = c("trunk")
  ) |> 
  osmdata_sf()

hy_roads1 <- opq(bbox = hy_bbox) |> 
  add_osm_feature(
    key = "highway", 
    value = c("motorway")
  ) |> 
  osmdata_sf()

hy_roads2 <- opq(bbox = hy_bbox) |> 
  add_osm_feature(
    key = "highway", 
    value = c("primary")
  ) |> 
  osmdata_sf()

hy_roads3 <- opq(bbox = hy_bbox) |> 
  add_osm_feature(
    key = "highway", 
    value = c("secondary")
  ) |> 
  osmdata_sf()

hy_roads4 <- opq(bbox = hy_bbox) |> 
  add_osm_feature(
    key = "highway", 
    value = c("tertiary")
  ) |> 
  osmdata_sf()

hy_roads5 <- opq(bbox = hy_bbox) |> 
  add_osm_feature(
    key = "highway", 
    value = c("unclassified")
  ) |> 
  osmdata_sf()

hy_map <- read_sf(here("data", "haryana_map", "HARYANA_DISTRICT_BDY.shp")) |> 
  st_transform(crs = 4326) |> 
  # as_tibble() |> 
  janitor::clean_names() |> 
  mutate(
    district = str_to_sentence(district),
    district = str_replace_all(district, ">", "a"),
    district = str_replace_all(district, "\\|", "i")
  )

Visualization Parameters

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

# Font for the caption
font_add_google("Stint Ultra Condensed",
  family = "caption_font"
) 

# Font for plot text
font_add_google("Saira Extra Condensed",
  family = "body_font"
) 

showtext_auto()

mypal <- paletteer::paletteer_d("futurevisions::cancri")
seecolor::print_color(mypal)

mypal <- paletteer::paletteer_d(
  "rcartocolor::ag_Sunset",
  direction = -1
)
mypal <- mypal[c(1, 3:7)]
mypal[6] <- darken(mypal[6], 0.6)
mypal
bg_col <- mypal[6]

text_col <- mypal[1]
text_hil <- mypal[1]

bts <- 120

# Caption stuff for the plot
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_title <- "Haryana: Roads and Highways"

plot_subtitle <- plot_subtitle <- glue::glue("Displaying <b style='color:{mypal[2]}'>Highways</b>, <b style='color:{mypal[3]}'>Primary</b>, <b style='color:{mypal[3]}'>Secondary</b> and <b style='color:{mypal[4]}'>Tertiary</b> Roads.")

plot_caption <- paste0(
  "**Data:** Open Street Maps", 
  " |  **Code:** ", 
  social_caption_1, 
  " |  **Graphics:** ", 
  social_caption_2
  )

rm(github, github_username, xtwitter, 
   xtwitter_username, social_caption_1, 
   social_caption_2)

The static plot

bts = 60

g <- ggplot() +
  
  # Outline Map of Haryana and districts
  geom_sf(
    data = hy_map,
    colour = mypal[1],
    fill = bg_col,
    linewidth = 0.2,
    linejoin = "round",
    alpha = 0.9
  ) +
  
  # Plotting Roads of Haryana 
  
  # Motorways
  geom_sf(
    data = hy_roads1$osm_lines |> 
            st_transform(crs = 4326) |> 
            st_intersection(hy_map),
    colour = mypal[2],
    alpha = 1,
    linewidth = 0.6,
    linetype = 1
  ) +
  
  # Trunk Roads
  geom_sf(
    data = hy_roads$osm_lines |> 
            st_transform(crs = 4326) |> 
            st_intersection(hy_map),
    colour = mypal[2],
    alpha = 1,
    linewidth = 0.5,
    linetype = 1
  ) +
  
  # Primary Roads
  geom_sf(
    data = hy_roads2$osm_lines |> 
            st_transform(crs = 4326) |> 
            st_intersection(hy_map),
    colour = mypal[3],
    alpha = 0.8,
    linewidth = 0.4,
    linetype = 1
  ) +
  
  # Secondary Roads
  geom_sf(
    data = hy_roads3$osm_lines |> 
            st_transform(crs = 4326) |> 
            st_intersection(hy_map),
    colour = mypal[3],
    alpha = 0.8,
    linewidth = 0.3,
    linetype = 1
  ) +
  
  # Tertiary Roads
  geom_sf(
    data = hy_roads4$osm_lines |> 
            st_transform(crs = 4326) |> 
            st_intersection(hy_map),
    colour = mypal[4],
    alpha = 0.7,
    linewidth = 0.2,
    linetype = 1
  ) +
  
  # Labels of the districts names
  geom_sf_text(
    data = hy_map,
    colour = text_col,
    mapping = aes(
      label = district
    ),
    size = bts/3,
    family = "body_font",
    alpha = 0.4
  ) +
  
  # Themes and Labels
  labs(
    title = plot_title,
    subtitle = plot_subtitle,
    caption = plot_caption
  ) +
  ggthemes::theme_map(
    base_size = bts,
    base_family = "body_font"
  ) + 
  theme(
    text = element_text(
      colour = text_hil
    ),
    plot.title = element_text(
      size = bts * 4.5,
      hjust = 0.5,
      face = "bold",
      margin = margin(5,0,5,0, "mm"),
      colour = text_hil,
      family = "title_font"
    ),
    plot.caption = element_textbox(
      colour = text_hil,
      hjust = 0.5,
      family = "body_font",
      margin = margin(0,0,0,0, "mm"),
      size = bts / 1.5
    ),
    plot.subtitle = element_textbox(
      colour = text_hil,
      hjust = 0.5,
      margin = margin(5,0,0,0, "mm"),
      size = 1.2 * bts
    ),
    plot.title.position = "plot",
    plot.margin = margin(10, -20, 10, -20, "mm")
  )

Savings the graphics

ggsave(
  filename = here::here("data_vizs", "roads_map_hy.png"),
  plot = g,
  width = 24, 
  height = 36,   
  units = "in",
  bg = "white"
)

ggsave(
  filename = here::here("data_vizs", "artist_roads_map_hy.png"),
  plot = g,
  width = 24 / 2, 
  height = 36 / 2,   
  units = "in",
  bg = mypal[6]
)

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

Using a different colour palette

Map of Haryana showing highways, roads, streets and connectivity.