Basic Maps

Contents

1. Introduction

2. Downloading Data

    2.1 Negation

    2.2 Additional key-value pairs

    2.3 A note on rivers

    2.4 Downloading with osm_structures and make_osm_map

          2.4.1 The london data of osmplotr

    2.5 Downloading connected highways

          2.5.1 connect_highways in detail

3. Producing maps

    3.1 Saving Maps

    3.2 Plotting different OSM Structures

    3.3. Automating map production

    3.4 Axes

1. Introduction

A map can be generated using the following simple steps:

library (osmplotr)
library (maptools) # Needed for this vignette

1. Specify the bounding box for the desired region

bbox <- get_bbox (c(-0.13,51.50,-0.11,51.52))

2. Download the desired data—in this case, all building perimeters.

dat_B <- extract_osm_objects (key='building', bbox=bbox)

3. Initiate an osm_basemap with desired background (bg) colour

map <- osm_basemap (bbox=bbox, bg='gray20')

4. Add desired plotting objects in the desired colour.

map <- add_osm_objects (map, dat_B, col='gray40')

5. Print the map

print_osm_map (map)

The function print_osm_map creates a graphics device that is scaled to the bounding box of the map. Note also that osmplotr maps contain no margins and fill the entire plot area. Additional capabilities of osmplotr are described in the following sections, beginning with downloading and extraction of data.

2. Downloading Data

The main function for downloading OSM data from the overpass API is extract_osm_objects. Data of a particular type can be extracted by passing the appropriate OSM key, as in the above example:

bbox <- get_bbox (c(-0.13,51.51,-0.11,51.52))
dat_B <- extract_osm_objects (key='building', bbox=bbox)
dat_H <- extract_osm_objects (key='highway', bbox=bbox)

These objects are of appropriate Spatial classes:

class (dat_B); class (dat_H)

## [1] "SpatialPolygonsDataFrame"
## attr(,"package")
## [1] "sp"

## [1] "SpatialLinesDataFrame"
## attr(,"package")
## [1] "sp"

The SpatialPolygonsDataFrame and SpatialLinesDataFrame of London buildings and highways respectively contain

length (dat_B); length (dat_H)

## [1] 2178

## [1] 2139

… 2,178 building polygons and 2,139 highway lines. extract_osm_objects also accepts key-value pairs which are passed to the overpass API :

dat_T <- extract_osm_objects (key='natural', value='tree', bbox=bbox)

Trees are located by single coordinates and are thus SpatialPoints:

class (dat_T); length (dat_T)

## [1] "SpatialPointsDataFrame"
## attr(,"package")
## [1] "sp"

## [1] 1310

2.1 Negation

Negation can be specified by pre-pending ! to the value argument so that, for example, all natural objects that are not trees can be extracted with

dat_NT <- extract_osm_objects (key='natural', value='!tree', bbox=bbox)

london$dat_H contains all non-primary highways, and was extracted with,

dat_H <- extract_osm_objects (key='highway', value='!primary', bbox=bbox)

2.2 Additional key-value pairs

Any number of key-value pairs may be passed to extract_osm_objects. For example, a named building can be extracted with

extra_pairs <- c ('name', 'Royal.Festival.Hall')
dat <- extract_osm_objects (key='building', extra_pairs=extra_pairs, 
                                       bbox=bbox)

This data is stored in london$dat_RFH. Note that periods or dots are used for whitespace, and in fact symbolise (in grep terms) any character whatsoever. The polygon of a building at a particular street address can be extracted with

extra_pairs <- list (c ('addr:street', 'Stamford.St'),
                     c ('addr:housenumber', '150'))
dat <- extract_osm_objects (key='building', extra_pairs=extra_pairs, 
                                      bbox=bbox)

This data is stored as london$dat_ST. Note that addresses generally require combining both addr:street with addr:housenumber.

2.3 A note on rivers

OSM objects are extracted within R through using the osmar package which does not currently handle the extraction of rivers in a failsafe way. Rivers are generally defined by (key,value)=('waterway','riverbank'), with relations returned as an OSM multipolygon. These multipolygon objects are, however, not extracted by osmar when they extend beyond a requested bbox, and there is no way to know in advance whether or not that may be the case. This requests to download river polygons may not yield the desired results. This problem will be addressed in future releases of osmplotr.

2.4 Downloading with osm_structures and make_osm_map

The functions osm_structures and make_osm_map aid both downloading multiple OSM data types and plotting (with the latter described below). osm_structures returns a data.frame of OSM structure types, associated key-value pairs, unique suffices which may be appended to data structures for storage purposes, and suggested colours. Passing this list to make_osm_map will return a list of the requested OSM data items, named through combining the dat_prefix specified in make_osm_map and the suffices specified in osm_structures.

osm_structures ()

##     structure      key value suffix      cols
## 1    building building           BU #646464FF
## 2     amenity  amenity            A #787878FF
## 3    waterway waterway            W #646478FF
## 4       grass  landuse grass      G #64A064FF
## 5     natural  natural            N #647864FF
## 6        park  leisure  park      P #647864FF
## 7     highway  highway            H #000000FF
## 8    boundary boundary           BO #C8C8C8FF
## 9        tree  natural  tree      T #64A064FF
## 10 background                          gray20

Many structures are identified by keys only, in which cases the values are empty strings.

osm_structures()$value [1:4]

## [1] ""      ""      ""      "grass"

The last row of osm_structures exists only to define the background colour of the map, as explained below (3.3. Automating map production).

The suffices include as many letters as are necessary to represent all unique structure names. make_osm_map returns a list of two components:

1. osm_data containing the data objects passed in the osm_structures argument. Any existing osm_data may also be submitted to make_osm_map, in which case any objects not present in the submitted data will be appended to the returned version. If osm_data is not submitted, all objects in osm_structures will be downloaded and returned.
2. map containing the ggplot2 map objects with layers overlaid according to the sequence and colour schemes specified in osm_structures

The data specified in osm_structures can then be downloaded simply by calling:

dat <- make_osm_map (structures=osm_structures (), bbox=bbox)

names (dat); sapply (dat, class); names (dat$osm_data)

## [1] "osm_data" "map"

## $osm_data
## [1] "list"
## 
## $map
## [1] "gg"     "ggplot"

## [1] "dat_BU" "dat_A"  "dat_W"  "dat_G"  "dat_N"  "dat_P"  "dat_H"  "dat_BO"
## [9] "dat_T"

The requested data are contained in dat$osm_data. A list of desired structures can also be passed to this function, for example,

osm_structures (structures=c('building', 'highway'))

##    structure      key value suffix      cols
## 1   building building            B #646464FF
## 2    highway  highway            H #000000FF
## 3 background                          gray20

Passing this to make_osm_map will download only these two structures. Finally, note that the example of,

osm_structures (structures='grass')

##    structure     key value suffix      cols
## 1      grass landuse grass      G #64A064FF
## 2 background                         gray20

demonstrates that osm_structures converts a number of common keys to OSM-appropriate key-value pairs.

structures <- c ('highway', 'highway', 'building', 'building', 'building',
                 'amenity', 'park', 'natural', 'tree')   
structs <- osm_structures (structures=structures, col_scheme='dark')   
structs$value [1] <- '!primary'   
structs$value [2] <- 'primary'
structs$suffix [2] <- 'HP'
structs$value [3] <- '!residential'
structs$value [4] <- 'residential'
structs$value [5] <- 'commercial'
structs$suffix [3] <- 'BNR'
structs$suffix [4] <- 'BR'
structs$suffix [5] <- 'BC'

london <- make_osm_map (structures=structs, bbox=bbox)
london <- london$osm_data

2.5 Downloading connected highways

The visualisation functions described in the second osmplotr vignette (Data maps) enable particular regions of maps to be highlighted. While it may often be desirable to highlight regions according to a user’s own data, osmplotr also enables regions to be defined by providing a list of the names of encircling highways. The function which achieves this is connect_highways, which returns a sequential list of SpatialPoints from those segments of the named highways which connected continuously and sequentially to form a single enclosed space. An example is,

highways <- c ('Monmouth.St', 'Short.?s.Gardens', 'Endell.St', 'Long.Acre',
               'Upper.Saint.Martin')
highways1 <- connect_highways (highways=highways, bbox=bbox)

Note the use of the regex character ? which declares that the previous character is optional. This matches both “Shorts Gardens” and “Short’s Gardens”, both of which appear in OSM data.

class (highways1); length (highways1); head (coordinates (highways1))

## [1] "SpatialPoints"
## attr(,"package")
## [1] "sp"

## [1] 55

##     coords.x1 coords.x2
## 14 -0.1250003  51.51480
## 15 -0.1254141  51.51457
## 16 -0.1257428  51.51440
## 17 -0.1259169  51.51430
## 18 -0.1260387  51.51424
## 19 -0.1269318  51.51381

Other examples, which are also included in the provided london data, include:

highways <- c ('Endell.St', 'High.Holborn', 'Drury.Lane', 'Long.Acre')
highways2 <- connect_highways (highways=highways, bbox=bbox)
highways <- c ('Drury.Lane', 'High.Holborn', 'Kingsway', 'Great.Queen.St')
highways3 <- connect_highways (highways=highways, bbox=bbox)

The extraction of bounding polygons from named highways is not failsafe, and may generate various warning messages. To understand the kinds of conditions under which it may not work, it is useful to examine connect_highways in more detail.

bbox_big <- get_bbox (c(-0.15,51.5,-0.10,51.52))
highways <- c ('Kingsway', 'Holborn', 'Farringdon.St', 'Strand',
               'Fleet.St', 'Aldwych')
highway_list <- connect_highways (highways=highways, bbox=bbox_big, plot=TRUE)

## Downloading OSM data ...
## 
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  |=================================================================| 100%

## Warning in get_highway_cycle(ways): Cycle unable to be extended through all
## ways

3. Producing maps

Maps will generally contain multiple kinds of OSM data, for example,

dat_B <- extract_osm_objects (key='building', bbox=bbox)
dat_H <- extract_osm_objects (key='highway', bbox=bbox)
dat_T <- extract_osm_objects (key='natural', value='tree', bbox=bbox)

As illustrated above, plotting maps requires first making a basemap with a specified background colour. Portions of maps can also be plotted by creating a basemap with a smaller bounding box.

bbox_small <- get_bbox (c(-0.13,51.51,-0.11,51.52))
map <- osm_basemap (bbox=bbox_small, bg='gray20')
map <- add_osm_objects (map, dat_H, col='gray70')
map <- add_osm_objects (map, dat_B, col='gray40')

map is then a ggplot2 which may be viewed simply by passing it to print_osm_map:

print_osm_map (map)

Other graphical parameters can also be passed to add_osm_objects, such as border colours or line widths and types. For example,

map <- osm_basemap (bbox=bbox_small, bg='gray20')
map <- add_osm_objects (map, dat_B, col='gray40', border='orange', size=0.2)
print_osm_map (map)

The size argument is passed to the corresponding ggplot2 routine for plotting polygons, lines, or points, and respectively determines widths of lines (for polygon outlines and for lines), and sizes of points. The col argument determines the fill colour of polygons, or the colour of lines or points.

map <- add_osm_objects (map, dat_H, col='gray70', size=0.7)
map <- add_osm_objects (map, dat_T, col='green', size=2, shape=1)
print_osm_map (map)

Note also that the shape parameter determines the point shape, for details of which see ?ggplot2::shape. Also note that plot order affects the final outcome, because components are sequentially overlaid and thus the same map components plotted in a different order will generally produce a different result.

3.1 Saving Maps

The function print_osm_map() can be used to print either to on-screen graphical devices or to graphics files (see, for example, ?png for a list of possible graphics devices). Sizes and resolutions of devices may be specified with the appropriate parameters. Device dimensions are scaled by default to the proportions of the bounding box (although this can be over-ridden).

A screen-based device simply requires

print_osm_map (map)

while examples of writing higher resolution versions to files include:

print_osm_map (map, filename="map.png", width=10, units="in", dpi=72)
print_osm_map (map, filename="map.eps", width=1000, units="px", dpi=72)
print_osm_map (map, filename="map", device="jpeg", width=10, units="cm")

3.2 Plotting different OSM Structures

The ability demonstrated above to use negation in extract-osm-objects allows different kinds of the same object to be visually contrasted, for example primary and non-primary highways:

dat_HP <- extract_osm_objects (key='highway', value='primary', bbox=bbox)
dat_H <- extract_osm_objects (key='highway', value='!primary', bbox=bbox)

map <- osm_basemap (bbox=bbox_small, bg='gray20')
map <- add_osm_objects (map, dat_H, col='gray50')
map <- add_osm_objects (map, dat_HP, col='gray80', size=2)
print_osm_map (map)

The additional key-value pairs demonstrated above (for Royal Festival Hall, dat_RFH and 150 Stamford Street, dat_ST) also demonstrated above allow for highly customised maps in which distinct objects are plotting with different colour schemes.

bbox_small2 <- get_bbox (c (-0.118, 51.504, -0.110, 51.507))
map <- osm_basemap (bbox=bbox_small2, bg='gray95')
map <- add_osm_objects (map, dat_H, col='gray80')
map <- add_osm_objects (map, dat_HP, col='gray60', size=2)
map <- add_osm_objects (map, dat_RFH, col='orange', border='red', size=2)
map <- add_osm_objects (map, dat_ST, col='skyblue', border='blue', size=2)
print_osm_map (map)

3.3. Automating map production

As indicated above (2.4 Downloading with osm_structures and make_osm_map), the production of maps overlaying various type of OSM objects is facilitated with make_osm_map. The structure of a map is defined by osm_structures as described above.

Producing a map with customised data is as simple as,

structs <- c ('highway', 'building', 'park', 'grass', 'tree')   
structures <- osm_structures (structures=structs, col_scheme='light')   
dat <- make_osm_map (structures=structures, bbox=bbox_small)
map <- dat$map
print_osm_map (map)

Calling make_osm_map() downloads the requested structures within the given bbox and returns a list of two components, the first of which contains the downloaded data:

names (dat); names (dat$osm_data)

## [1] "osm_data" "map"

## [1] "dat_B" "dat_H" "dat_P" "dat_A" "dat_G" "dat_T"

Pre-downloaded data may also be passed to make_osm_map()

dat <- make_osm_map (structures=structures, osm_data=dat$osm_data)
print_osm_map (dat$map)

In this case, because no bounding box was passed to make_osm_map, a bounding box is extracted as the largest box spanning all objects in osm_data. These objects include highways which extend beyond the defining bounding box, and the large park in the south east. The bbox argument may simply be passed to restore this map to the previous version:

dat <- make_osm_map (structures=structures, osm_data=dat$osm_data,
                     bbox=bbox_small)

Objects in maps are overlaid on the plot according to the order of rows in osm_structures, with the single exception that background is plotted first. This order can be readily changed or restricted simply by submitting structures in a desired order.

structs <- c ('amenity', 'building', 'grass', 'highway', 'park')
osm_structures (structs, col_scheme='light')

##    structure      key value suffix      cols
## 1    amenity  amenity            A #DCDCDCFF
## 2   building building            B #C8C8C8FF
## 3      grass  landuse grass      G #C8FFC8FF
## 4    highway  highway            H #969696FF
## 5       park  leisure  park      P #C8DCC8FF
## 6 background                          gray95

3.4 Axes

Axes may be added to maps using the add_axes function. In contrast to many R packages for producing maps, maps in osmplotr fill the entire plotting space, and axes are added internal to this space. The separate function for adding axes allows them to be overlaid on top of all previous layers.

Axes added to a dark version of the previous map look like this:

structures <- osm_structures (structures=structs, col_scheme='dark')   
dat <- make_osm_map (structures=structures, osm_data=dat$osm_dat,
                     bbox=bbox_small)
map <- add_axes (dat$map, colour='black')

Note that, as described above, make_osm_map returns a list of two items: (i) potentially modified data (in $osm_data) and (ii) the map object (in $map). All other add_ functions take a map object as one argument and return the single value of the modified map object.

print_osm_map (map)

This map reveals that the axes and labels are printed above semi-transparent background rectangles, with transparency controlled by the alpha parameter. Axes are always plotted on the left and lower side, but positions can be adjusted with the pos parameter which specifies the,

Positions of axes and labels relative to entire plot device

map <- add_axes (map, colour='blue', pos=c(0.1,0.2),
                      fontsize=5, fontface=3, fontfamily="Times")
print_osm_map (map)

The second call to add_axes overlaid additional axes on a map that already had axes from the previous call. This call also demonstrates how sizes and other font characteristics of text labels can be specified.

Finally, the current version of osmplotr does not allow text labels of axes to be rotated. (This is because the semi-transparent underlays are generated with ggplot2::geom_label which currently prevents rotation.)

Click on the following link to proceed to the second osmplotr vignette: Data maps