tmaptools (version 1.2-4)

read_osm: Read Open Street Map data

Description

Read Open Street Map data. Either OSM tiles are read and returned as a spatial raster, or vectorized OSM data are queried and returned as spatial polygons, lines, and/or points.

Usage

read_osm(x, raster = NA, zoom = NULL, type = "osm", minNumTiles = NULL,
  mergeTiles = NULL, ...)
osm_poly(query)
osm_line(query)
osm_point(query)

Arguments

x

object that can be coerced to a bounding box with bb (e.g. an existing bounding box or a shape), or an osmar object. In the first case, other arguments can be passed on to bb (see ...). If an existing bounding box is specified in projected coordinates, please specify current.projection.

raster

logical that determines whether a raster or vector shapes are returned. In the latter case, specify the vector selections (see argument ...). By default, raster=TRUE if no vector selections are made, and raster=FALSE otherwise.

zoom

passed on to openmap. Only applicable when raster=TRUE.

type

tile provider, by default "osm", which corresponds to OpenStreetMap Mapnik. See openmap for options. Only applicable when raster=TRUE.

minNumTiles

passed on to openmap Only applicable when raster=TRUE.

mergeTiles

passed on to openmap Only applicable when raster=TRUE.

...

arguments passed on to bb, or arguments that specify polygons, lines, and/or points queries, created with osm_poly, osm_line, and osm_point respectively.

query

query to select polygons, lines, or points. Currently, two formats are supported: 1) key, 2) key=value. See http://wiki.openstreetmap.org/wiki/Map_Features for Open Street Map keys and values.

Value

The output of read_osm is a SpatialGridDataFrame if raster=TRUE, and otherwise a named list of SpatialPolygonsDataFrame, SpatialLinesDataFrame, and/or SpatialPointsDataFrame objects. The names of this list are the names of arguments defined at ....

References

Tennekes, M., 2018, tmap: Thematic Maps in R, Journal of Statistical Software, 84(6), 1-39, DOI

Examples

# NOT RUN {
if (require(tmap)) {
    #### Choropleth with OSM background

    # load Netherlands shape
    data(NLD_muni)

    # read OSM raster data
    osm_NLD <- read_osm(NLD_muni, ext=1.1)

    # plot with regular tmap functions
    tm_shape(osm_NLD) +
    	tm_raster() +
    tm_shape(NLD_muni) +
    	tm_polygons("population", convert2density=TRUE, style="kmeans", alpha=.7, palette="Purples")

    #### A close look at the building of Statistics Netherlands in Heerlen

    # create a bounding box around the CBS (Statistics Netherlands) building
    CBS_bb <- bb("CBS Weg 11, Heerlen", width=.003, height=.002)

    # read Microsoft Bing satellite and OpenCycleMap OSM layers
    CBS_osm1 <- read_osm(CBS_bb, type="bing")
    CBS_osm2 <- read_osm(CBS_bb, type="opencyclemap")

    # plot OSM raster data
    qtm(CBS_osm1)
    qtm(CBS_osm2)

    # read vectorized OSM data
    CBS_osm3 <- read_osm(CBS_bb,
        roads=osm_line("highway"),
        parking=osm_poly("amenity=parking"),
        building=osm_poly("building"),
        park=osm_poly("leisure=park"),
        railway_area=osm_poly("landuse=railway"),
        railway=osm_line("railway"),
        forest=osm_poly("landuse=forest"),
        grass=osm_poly("landuse=grass"),
        bicycle=osm_line("highway=cycleway"))

    # plot vectorized OSM data
    tm_shape(CBS_osm3$grass, bbox=CBS_bb) + tm_polygons("darkolivegreen3") +
        tm_shape(CBS_osm3$forest) + tm_fill("forestgreen") +
        tm_shape(CBS_osm3$railway_area) + tm_fill(col="grey70") +
        tm_shape(CBS_osm3$parking) + tm_polygons("gold") +
        tm_shape(CBS_osm3$building) + tm_polygons("grey50") +
        tm_shape(CBS_osm3$roads, bbox=CBS_bb) + tm_lines(col="gold", lwd=3) +
        tm_shape(CBS_osm3$bicycle) + tm_lines(col="blue", lwd=3) +
        tm_shape(CBS_osm3$railway) + tm_lines(col="grey20", lwd=3, lty="dashed") +
        tm_layout(bg.color="grey90")
}
# }