Lines and Shapes
Leaflet makes it easy to take spatial lines and shapes from R and add them to maps.
Polygons and Polylines
Line and polygon data can come from a variety of sources:
Polygonobjects (from the
Lineobjects (from the
LINESTRINGobjects (from the
mapobjects (from the
map(fill = TRUE)for polygons,
- Two-column numeric matrix; the first column is longitude and the second is latitude. Polygons are separated by rows of
(NA, NA). It is not possible to represent multi-polygons nor polygons with holes using this method; use
library(rgdal) # From https://www.census.gov/geo/maps-data/data/cbf/cbf_state.html states <- readOGR("shp/cb_2013_us_state_20m.shp", layer = "cb_2013_us_state_20m", GDAL1_integer64_policy = TRUE)
## OGR data source with driver: ESRI Shapefile ## Source: "shp/cb_2013_us_state_20m.shp", layer: "cb_2013_us_state_20m" ## with 52 features ## It has 9 fields ## Integer64 fields read as doubles: ALAND AWATER
neStates <- subset(states, states$STUSPS %in% c( "CT","ME","MA","NH","RI","VT","NY","NJ","PA" )) leaflet(neStates) %>% addPolygons(color = "#444444", weight = 1, smoothFactor = 0.5, opacity = 1.0, fillOpacity = 0.5, fillColor = ~colorQuantile("YlOrRd", ALAND)(ALAND), highlightOptions = highlightOptions(color = "white", weight = 2, bringToFront = TRUE))
The above example uses the
highlightOptions parameter to emphasize the currently moused-over polygon. (The
bringToFront = TRUE argument is necessary to prevent the thicker, white border of the active polygon from being hidden behind the borders of other polygons that happen to be higher in the z-order.) You can use
highlightOptions with all of the shape layers described on this page.
Simplifying complex polygons/polylines
Very detailed (i.e. large) shape data can present a problem for Leafet, since it is all eventually passed into the browser and rendered as SVG, which is very expressive and convenient but has scalability limits. In these cases, consider using
rmapshaper::ms_simplify, which does topology-preserving simplification conveniently from R.
library(albersusa) fullsize <- usa_composite() object.size(fullsize)
## 1265256 bytes
simplified <- rmapshaper::ms_simplify(fullsize) object.size(simplified)
## 262608 bytes
Circles are added using
addCircles(). Circles are similar to circle markers; the only difference is that circles have their radii specified in meters, while circle markers are specified in pixels. As a result, circles are scaled with the map as the user zooms in and out, while circle markers remain a constant size on the screen regardless of zoom level.
When plotting circles, only the circle centers (and radii) are required, so the set of valid data sources is different than for polygons and the same as for markers. See the introduction to Markers for specifics.
cities <- read.csv(textConnection(" City,Lat,Long,Pop Boston,42.3601,-71.0589,645966 Hartford,41.7627,-72.6743,125017 New York City,40.7127,-74.0059,8406000 Philadelphia,39.9500,-75.1667,1553000 Pittsburgh,40.4397,-79.9764,305841 Providence,41.8236,-71.4222,177994 ")) leaflet(cities) %>% addTiles() %>% addCircles(lng = ~Long, lat = ~Lat, weight = 1, radius = ~sqrt(Pop) * 30, popup = ~City )
Rectangles are added using the
addRectangles() function. It takes
lat2 vector arguments that define the corners of the rectangles. These arguments are always required; the rectangle geometry cannot be inferred from the data object.
leaflet() %>% addTiles() %>% addRectangles( lng1=-118.456554, lat1=34.078039, lng2=-118.436383, lat2=34.062717, fillColor = "transparent" )