osmdata & ggplot: the street maps
Apr 24, 2022
Street Maps by osmdata and ggplot
1 Library
library(tidyverse)
library(osmdata) # package for working with streets
library(showtext) # for custom fonts
library(ggmap)
library(rvest)2 OSM Data
# The avilable_tags() function shows you the available features of the different classifications of streets and other map features this package works with
available_tags("highway")## [1] "bridleway" "bus_guideway" "bus_stop"
## [4] "busway" "construction" "corridor"
## [7] "crossing" "cycleway" "elevator"
## [10] "emergency_access_point" "emergency_bay" "escape"
## [13] "footway" "give_way" "living_street"
## [16] "milestone" "mini_roundabout" "motorway"
## [19] "motorway_junction" "motorway_link" "passing_place"
## [22] "path" "pedestrian" "platform"
## [25] "primary" "primary_link" "proposed"
## [28] "raceway" "residential" "rest_area"
## [31] "road" "secondary" "secondary_link"
## [34] "service" "services" "speed_camera"
## [37] "steps" "stop" "street_lamp"
## [40] "tertiary" "tertiary_link" "toll_gantry"
## [43] "track" "traffic_mirror" "traffic_signals"
## [46] "trailhead" "trunk" "trunk_link"
## [49] "turning_circle" "turning_loop" "unclassified"2.1 Location
# We can then use getbb() to return the geographic location of a city simply by passing it a string.
getbb("Atlanta Georgia")## min max
## x -84.55107 -84.28956
## y 33.64781 33.886822.2 Highway
# grab certain categories of streets from this package
big_streets <- getbb("Asheville United States")%>%
opq()%>%
add_osm_feature(key = "highway",
value = c("motorway", "primary", "motorway_link", "primary_link")) %>%
osmdata_sf() # format that ggmap know
big_streetsView(big_streets[["osm_lines"]])# grab two more dataframes of streets: medium streets and small streets
med_streets <- getbb("Asheville United States")%>%
opq()%>%
add_osm_feature(key = "highway",
value = c("secondary", "tertiary", "secondary_link", "tertiary_link")) %>%
osmdata_sf()
small_streets <- getbb("Asheville United States")%>%
opq()%>%
add_osm_feature(key = "highway",
value = c("residential", "living_street",
"unclassified",
"service", "footway"
)) %>%
osmdata_sf()2.3 Waterway
river <- getbb("Asheville United States")%>%
opq()%>%
add_osm_feature(key = "waterway", value = "river") %>%
osmdata_sf()2.4 Railway
railway <- getbb("Asheville United States")%>%
opq()%>%
add_osm_feature(key = "railway", value="rail") %>%
osmdata_sf()available_tags("railway")## [1] "abandoned" "buffer_stop" "crossing" "derail"
## [5] "disused" "funicular" "halt" "level_crossing"
## [9] "light_rail" "miniature" "monorail" "narrow_gauge"
## [13] "platform" "preserved" "rail" "railway_crossing"
## [17] "razed" "roundhouse" "signal" "station"
## [21] "subway" "subway_entrance" "switch" "tram"
## [25] "tram_stop" "traverser" "turntable" "wash"
## [29] "water_crane"3 Plot
3.1 Plot big street
ggplot() +
geom_sf(data = big_streets$osm_lines,
inherit.aes = FALSE,
color = "black")
3.2 Plot river
ggplot() +
geom_sf(data = river$osm_lines,
inherit.aes = FALSE,
color = "black")
3.3 Plot big street & river
3.3.1 Combination
ggplot() +
geom_sf(data = big_streets$osm_lines,
inherit.aes = FALSE,
color = "black") +
geom_sf(data = river$osm_lines,
inherit.aes = FALSE,
color = "black")
3.3.2 Adjust size
Note: the axes are far too large because of the river. Let’s limit them using coord_sf().
ggplot() +
geom_sf(data = big_streets$osm_lines,
inherit.aes = FALSE,
color = "black") +
geom_sf(data = river$osm_lines,
inherit.aes = FALSE,
color = "black") +
coord_sf(xlim = c(-82.65, -82.48),
ylim = c(35.5, 35.65)) # Zoom in data, X-Y value see: getbb("Atlanta Georgia")
3.3.3 Add other features
Let’s add the remaining features as well as some coloring, size, and alpha aesthetics.
ggplot() +
geom_sf(data = river$osm_lines,
inherit.aes = FALSE,
color = "steelblue",
size = .8,
alpha = .3) +
geom_sf(data = railway$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .2,
linetype="dotdash",
alpha = .5) +
geom_sf(data = med_streets$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .3,
alpha = .5) +
geom_sf(data = small_streets$osm_lines,
inherit.aes = FALSE,
color = "#666666",
size = .2,
alpha = .3) +
geom_sf(data = big_streets$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .5,
alpha = .6) +
coord_sf(xlim = c(-82.65, -82.48),
ylim = c(35.5, 35.65))
NB: the order in which you layer the features (e.g., river before the streets) really makes a difference and can be altered.
3.3.4 Add custom fonts and label the map
font_add_google(name = "Lato", family = "lato") # add custom fonts
showtext_auto()ggplot() +
geom_sf(data = river$osm_lines,
inherit.aes = FALSE,
color = "steelblue",
size = .8,
alpha = .3) +
geom_sf(data = railway$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .2,
linetype="dotdash",
alpha = .5) +
geom_sf(data = med_streets$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .3,
alpha = .5) +
geom_sf(data = small_streets$osm_lines,
inherit.aes = FALSE,
color = "#666666",
size = .2,
alpha = .3) +
geom_sf(data = big_streets$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .5,
alpha = .6) +
coord_sf(xlim = c(-82.65, -82.48),
ylim = c(35.5, 35.65)) +
theme_void() + # get rid of background color, grid lines, etc.
theme(plot.title = element_text(size = 20, family = "lato", face="bold", hjust=.5),
plot.subtitle = element_text(family = "lato", size = 8, hjust=.5, margin=margin(2, 0, 5, 0))) +
labs(title = "ASHEVILLE", subtitle = "35.595°N / 82.552°W")
# save it
ggsave(file = "asheville.pdf", units = "in", width = 6, height = 7)4 Extensions
4.1 Highlighting individual streets
# Extract the famous Blue Ridge Parkway:
blue_ridge <- med_streets[["osm_lines"]] %>%
filter(name=="Blue Ridge Parkway")ggplot() +
geom_sf(data = river$osm_lines,
inherit.aes = FALSE,
color = "steelblue",
size = .8,
alpha = .3) +
geom_sf(data = railway$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .2,
linetype="dotdash",
alpha = .5) +
geom_sf(data = med_streets$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .3,
alpha = .5) +
geom_sf(data = small_streets$osm_lines,
inherit.aes = FALSE,
color = "#666666",
size = .2,
alpha = .3) +
geom_sf(data = big_streets$osm_lines,
inherit.aes = FALSE,
color = "black",
size = .5,
alpha = .6) +
geom_sf(data = blue_ridge, # Add Blue Ridge street
inherit.aes = FALSE,
color = "orange",
size = 1,
alpha = 1) +
coord_sf(xlim = c(-82.65, -82.45),
ylim = c(35.5, 35.65)) +
theme_void()
4.2 Adding other external geo data
To be continued: how to use “rvest”