tmaptools (version 1.2)

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, plesae 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 ....

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")
# }
# ## End(Not run)