knitr::opts_chunk$set ( collapse = TRUE, warning = TRUE, message = TRUE, width = 120, comment = "#>", fig.retina = 2, fig.path = "README-" )
R package to produce visually impressive customisable images of OpenStreetMap
(OSM) data downloaded internally from the
overpass api. The above map was produced directly
from osmplotr
with no further modification. This README
briefly demonstrates
the following functionality:
4. Highlighting Selected Areas
6. Highlighting Areas Bounded by Named Highways
But first the easy steps to map making:
library (osmplotr)
r
bbox <- get_bbox (c (-0.15, 51.5, -0.10, 51.52))
r
dat_B <- extract_osm_objects (key = "building", bbox = bbox)
osm_basemap
with desired background (bg
) colour
r
map <- osm_basemap (bbox = bbox, bg = "gray20")
r
map <- add_osm_objects (map, dat_B, col = "gray40")
r
print_osm_map (map)
library (osmdata) bbox <- get_bbox (c (-0.15, 51.5, -0.10, 51.52)) q0 <- opq (bbox) q1 <- add_osm_feature (q0, key = "building") dat_B <- osmdata_sf (q1, quiet = FALSE)$osm_polygons q1 <- add_osm_feature (q0, key = "highway") dat_H <- osmdata_sf (q1, quiet = FALSE)$osm_lines q1 <- add_osm_feature (q0, key = "leisure", value = "park") dat_P <- osmdata_sf (q1, quiet = FALSE)$osm_polygons q1 <- add_osm_feature (q0, key = "landuse", value = "grass") dat_G <- osmdata_sf (q1, quiet = FALSE)$osm_polygons london2 <- list (dat_B = dat_B, dat_H = dat_H, dat_P = dat_P, dat_G = dat_G) save (london2, file = "london2.rda")
First install the package
install.packages ("osmplotr")
or the development version
devtools::install_github ("ropensci/osmplotr")
And then load it in the usual way
library (osmplotr)
Simple maps can be made by overlaying different kinds of OSM data in different colours:
dat_H <- extract_osm_objects (key = "highway", bbox = bbox) dat_P <- extract_osm_objects (key = "park", bbox = bbox) dat_G <- extract_osm_objects (key = "landuse", value = "grass", bbox = bbox)
load ("london2.rda") dat_B <- london2$dat_B dat_H <- london2$dat_H dat_G <- london2$dat_G dat_P <- london2$dat_P
map <- osm_basemap (bbox = bbox, bg = "gray20") map <- add_osm_objects (map, dat_B, col = "gray40") map <- add_osm_objects (map, dat_H, col = "gray80") map <- add_osm_objects (map, dat_P, col = "darkseagreen") map <- add_osm_objects (map, dat_G, col = "darkseagreen1") print_osm_map (map)
print_osm_map (map, file = "map2.png", width = 600, units = "px", dpi = 72)
osmplotr
is primarily intended as a data visualisation tool, particularly
through enabling selected regions to be highlighted. Regions can be defined
according to simple point boundaries:
pts <- sp::SpatialPoints (cbind ( c (-0.115, -0.13, -0.13, -0.115), c (51.505, 51.505, 51.515, 51.515) ))
OSM objects within the defined regions can then be highlighted with different
colour schemes. cols
defines colours for each group (with only one here),
while bg
defines the colour of the remaining, background area.
map <- osm_basemap (bbox = bbox, bg = "gray20") map <- add_osm_groups (map, dat_B, groups = pts, cols = "orange", bg = "gray40") map <- add_osm_objects (map, london$dat_P, col = "darkseagreen1") map <- add_osm_groups ( map, london$dat_P, groups = pts, cols = "darkseagreen1", bg = "darkseagreen", boundary = 0 ) print_osm_map (map)
print_osm_map (map, filename = "map3.png", width = 600, units = "px", dpi = 72)
Note the border = 0
argument on the last call divides the park polygons
precisely along the border. The same map highlighted in dark-on-light:
map <- osm_basemap (bbox = bbox, bg = "gray95") map <- add_osm_groups (map, dat_B, groups = pts, cols = "gray40", bg = "gray85") map <- add_osm_groups (map, dat_H, groups = pts, cols = "gray20", bg = "gray70") print_osm_map (map)
print_osm_map (map, filename = "map4.png", width = 600, units = "px", dpi = 72)
add_osm_groups
also enables plotting an entire region as a group of
spatially distinct clusters of defined colours. Groups can be defined by simple
spatial points denoting their centres:
set.seed (2) ngroups <- 12 x <- bbox [1, 1] + runif (ngroups) * diff (bbox [1, ]) y <- bbox [2, 1] + runif (ngroups) * diff (bbox [2, ]) groups <- cbind (x, y) groups <- apply (groups, 1, function (i) { sp::SpatialPoints (matrix (i, nrow = 1, ncol = 2)) })
Calling add_osm_groups
with no bg
argument forces all points lying outside
those defined groups to be allocated to the nearest groups, and thus produces an
inclusive grouping extending across an entire region.
map <- osm_basemap (bbox = bbox, bg = "gray20") map <- add_osm_groups ( map, dat_B, groups = groups, cols = rainbow (length (groups)), border_width = 2 ) print_osm_map (map)
print_osm_map (map, filename = "map5.png", width = 600, units = "px", dpi = 72)
An alternative way of defining highlighted groups is by naming the highways encircling desired regions.
# These highways extend beyond the previous, smaller bbox bbox_big <- get_bbox (c (-0.15, 51.5, -0.10, 51.52)) highways <- c ( "Davies.St", "Berkeley.Sq", "Berkeley.St", "Piccadilly", "Regent.St", "Oxford.St" ) highways1 <- connect_highways (highways = highways, bbox = bbox_big) highways <- c ("Regent.St", "Oxford.St", "Shaftesbury") highways2 <- connect_highways (highways = highways, bbox = bbox_big) highways <- c ( "Piccadilly", "Shaftesbury.Ave", "Charing.Cross.R", "Saint.Martin", "Trafalgar.Sq", "Cockspur.St", "Pall.Mall", "St.James" ) highways3 <- connect_highways (highways = highways, bbox = bbox_big) highways <- c ( "Charing.Cross", "Duncannon.St", "Strand", "Aldwych", "Kingsway", "High.Holborn", "Shaftesbury.Ave" ) highways4 <- connect_highways (highways = highways, bbox = bbox_big) highways <- c ( "Kingsway", "Holborn", "Farringdon.St", "Strand", "Fleet.St", "Aldwych" ) highways5 <- connect_highways (highways = highways, bbox = bbox_big) groups <- list (highways1, highways2, highways3, highways4, highways5)
And then passing these lists of groups returned by connect_highways
to
add_osm_groups
, this time with some Wes Anderson flair.
map <- osm_basemap (bbox = bbox, bg = "gray20") library (wesanderson) cols <- wes_palette ("Darjeeling", 5) map <- add_osm_groups ( map, dat_B, groups = groups, boundary = 1, cols = cols, bg = "gray40", colmat = FALSE ) map <- add_osm_groups ( map, dat_H, groups = groups, boundary = 0, cols = cols, bg = "gray70", colmat = FALSE ) print_osm_map (map)
print_osm_map (map, filename = "map6.png", width = 600, units = "px", dpi = 72)
Finally, osmplotr
contains a function add_osm_surface
that spatially
interpolates a given set of spatial data points and colours OSM objects
according to a specified colour gradient. This is illustrated here with the
volcano
data projected onto the bbox
.
x <- seq (bbox [1, 1], bbox [1, 2], length.out = dim (volcano) [1]) y <- seq (bbox [2, 1], bbox [2, 2], length.out = dim (volcano) [2]) xy <- cbind (rep (x, dim (volcano) [2]), rep (y, each = dim (volcano) [1])) z <- as.numeric (volcano) dat <- data.frame (x = xy [, 1], y = xy [, 2], z = z)
map <- osm_basemap (bbox = bbox, bg = "gray20") cols <- gray (0:50 / 50) map <- add_osm_surface (map, dat_B, dat = dat, cols = cols) # Darken cols by ~20% map <- add_osm_surface ( map, dat_H, dat = dat, cols = adjust_colours (cols, -0.2) ) map <- add_colourbar (map, cols = cols, zlims = range (volcano)) map <- add_axes (map) print_osm_map (map)
print_osm_map (map, filename = "map7.png", width = 600, units = "px", dpi = 72)
# This is map1 used as the title # extrafont::loadfonts () lab_dat <- data.frame ( x = mean (bbox [1, ]), y = mean (bbox [2, ]), lab = "osmplotr" ) aes <- ggplot2::aes (x, y, label = lab) bbox <- get_bbox (c (-0.15, 51.5, -0.10, 51.52)) map <- osm_basemap (bbox = bbox, bg = "gray20") cols <- gray (0:50 / 50) map <- add_osm_surface (map, dat_B, dat = dat, cols = cols) map <- add_osm_surface ( map, dat_H, dat = dat, cols = adjust_colours (cols, -0.2) ) # map2 <- map + ggplot2::geom_text (dat = dat, mapping = aes, size = 60, # colour = "white", # family = "Lato Light", nudge_y = 0.0015) map2 <- map + ggplot2::geom_text ( dat = lab_dat, mapping = aes, size = 45, colour = "black", family = "Purisa", fontface = 2, nudge_y = 0.0005, nudge_x = 0.0005 ) map2 <- map2 + ggplot2::geom_text ( dat = lab_dat, mapping = aes, size = 45, colour = "white", family = "Purisa", nudge_y = 0.001, fontface = 2 ) print_osm_map (map2, filename = "map1.png", width = 800, units = "px", dpi = 72 )
Got a nice osmplotr
map? Please contribute in one of the following ways:
Fork repo, add link to README.md/.Rmd
, and send pull request; or
Open issue with details; or
Send email to address in
DESCRIPTION
.
See package vignettes
(basic maps and
data maps) for a
lot more detail and further capabilities of osmplotr
. Please note that this
project is released with a Contributor Code of Conduct. By
participating in this project you agree to abide by its terms.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.