# sp Gallery

# Plotting maps with `sp`

This document shows example images created with objects represented by one of the classes for spatial data in packages sp.

## Loading data and packages

The Meuse data set is loaded using a demo script in package `sp`,

    library(sp)
    demo(meuse, ask = FALSE, echo = FALSE) # loads the meuse data sets
    class(meuse)

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

The North Carolina SIDS (sudden infant death syndrome) data set is available from package `sf`, and is loaded by

    library(sf)

    ## Linking to GEOS 3.12.1, GDAL 3.8.4, PROJ 9.4.0; sf_use_s2() is TRUE

    nc <- as(st_read(system.file("gpkg/nc.gpkg", package="sf")), "Spatial")

    ## Reading layer `nc.gpkg' from data source
    ##   `/home/edzer/R/x86_64-pc-linux-gnu-library/4.4/sf/gpkg/nc.gpkg'
    ##   using driver `GPKG'
    ## Simple feature collection with 100 features and 14 fields
    ## Geometry type: MULTIPOLYGON
    ## Dimension:     XY
    ## Bounding box:  xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
    ## Geodetic CRS:  NAD27

## Using base plot

The basic `plot` command on a `Spatial` object gives just the geometry, without axes:

    plot(meuse)

axes can be added when `axes=TRUE` is given; plot elements can be added incrementally:

    plot(meuse, pch = 1, cex = sqrt(meuse$zinc)/12, axes = TRUE)
    v = c(100,200,400,800,1600)
    legend("topleft", legend = v, pch = 1, pt.cex = sqrt(v)/12)
    plot(meuse.riv, add = TRUE, col = grey(.9, alpha = .5))

For local projection systems, such as in this case

    proj4string(meuse)

    ## [1] "+proj=sterea +lat_0=52.1561605555556 +lon_0=5.38763888888889 +k=0.9999079 +x_0=155000 +y_0=463000 +ellps=bessel +units=m +no_defs"

the aspect ratio is set to 1, to make sure that one unit north equals one unit east. Even if the data are in long/lat degrees, an aspect ratio is chosen such that in the middle of the plot one unit north approximates one unit east. For small regions, this works pretty well; also note the degree symbols in the axes tic marks:

    crs.longlat = CRS("+init=epsg:4326")

    ## Warning in CPL_crs_from_input(x): GDAL Message 1: +init=epsg:XXXX syntax is
    ## deprecated. It might return a CRS with a non-EPSG compliant axis order.

    meuse.longlat = spTransform(meuse, crs.longlat)
    plot(meuse.longlat, axes = TRUE)

which looks different from the plot where one degree north (latitude) equals one degree east (longitude):

    par(mar = rep(0,4))
    plot(meuse.longlat, asp = 1)

## Graticules

Instead of axes with ticks and tick marks, maps often have graticules, a grid with constant longitude and latitude lines. `sp` provides several helper functions to add graticules, either in the local reference system, or in long/lat. Here is an example of the local reference system:

    par(mar = c(0, 0, 1, 0))
    library(methods) # as
    plot(as(meuse, "Spatial"), expandBB = c(.05, 0, 0, 0))
    plot(gridlines(meuse), add = TRUE, col = grey(.8))
    plot(meuse, add = TRUE)
    text(labels(gridlines(meuse)), col = grey(.7))
    title("default gridlines with Meuse projected data")

    par(mar = c(0, 0, 1, 0))
    grd <- gridlines(meuse.longlat)
    grd_x <- spTransform(grd, CRS(proj4string(meuse)))
    plot(as(meuse, "Spatial"), expandBB = c(.05, 0, 0, 0))
    plot(grd_x, add=TRUE, col = grey(.8))
    plot(meuse, add = TRUE)
    text(labels(grd_x, crs.longlat), col = grey(.7))

    ## Warning in labels.SpatialLines(grd_x, crs.longlat): this labels method is meant
    ## to operate on SpatialLines created with sp::gridlines

    title("longitude latitude gridlines and labels")

These lines look pretty straight, because it concerns a small area. For

    # demonstrate axis labels with angle, both sides:

    maps2sp = function(xlim, ylim, l.out = 100, clip = TRUE) {
        stopifnot(require(maps))
        m = map(xlim = xlim, ylim = ylim, plot = FALSE, fill = TRUE)
        as(st_as_sf(m), "Spatial")
    }
    par(mar = c(0, 0, 1, 0))
    m = maps2sp(c(-100,-20), c(10,55))

    ## Loading required package: maps

    sp = SpatialPoints(rbind(c(-101,9), c(-101,55), c(-19,9), c(-19,55)), CRS("+init=epsg:4326"))
    laea = CRS("+proj=laea +lat_0=30 +lon_0=-40")
    m.laea = spTransform(m, laea)
    sp.laea = spTransform(sp, laea)
    plot(as(m.laea, "Spatial"), expandBB = c(.1, 0.05, .1, .1))
    plot(m.laea, col = grey(.8), add = TRUE)
    gl = gridlines(sp, easts = c(-100,-80,-60,-40,-20), norths = c(20,30,40,50))
    gl.laea = spTransform(gl, laea)
    plot(gl.laea, add = TRUE)
    text(labels(gl.laea, crs.longlat))

    ## Warning in labels.SpatialLines(gl.laea, crs.longlat): this labels method is
    ## meant to operate on SpatialLines created with sp::gridlines

    text(labels(gl.laea, crs.longlat, side = 3:4), col = 'red')

    ## Warning in labels.SpatialLines(gl.laea, crs.longlat, side = 3:4): this labels
    ## method is meant to operate on SpatialLines created with sp::gridlines

    title("curved text label demo")

    # polar:
    par(mar = c(0, 0, 1, 0))
    pts=SpatialPoints(rbind(c(-180,-70),c(0,-70),c(180,-89),c(180,-70)), CRS("+init=epsg:4326"))
    gl = gridlines(pts, easts = seq(-180,180,20), ndiscr = 100)
    polar = CRS("+init=epsg:3031")
    plot(spTransform(pts, polar), expandBB = c(.05, 0, .05, 0))
    gl.polar = spTransform(gl, polar)
    lines(gl.polar)
    l = labels(gl.polar, crs.longlat, side = 3)

    ## Warning in labels.SpatialLines(gl.polar, crs.longlat, side = 3): this labels
    ## method is meant to operate on SpatialLines created with sp::gridlines

    l$pos = NULL # pos is too simple, use adj:
    text(l, adj = c(0.5, -0.5), cex = .8)
    l = labels(gl.polar, crs.longlat, side = 4)

    ## Warning in labels.SpatialLines(gl.polar, crs.longlat, side = 4): this labels
    ## method is meant to operate on SpatialLines created with sp::gridlines

    l$srt = 0 # otherwise they end up upside-down
    text(l, cex = .8)
    title("grid line labels on polar projection, epsg 3031")

    par(mar = c(0, 0, 1, 0))
    m = maps2sp(xlim = c(-180,180), ylim = c(-90,-70), clip = FALSE)
    gl = gridlines(m, easts = seq(-180,180,20))
    polar = CRS("+init=epsg:3031")
    gl.polar = spTransform(gl, polar)
    plot(as(gl.polar, "Spatial"), expandBB = c(.05, 0, .05, 0))
    plot(gl.polar, add = TRUE)
    plot(spTransform(m, polar), add = TRUE, col = grey(0.8, 0.8))
    l = labels(gl.polar, crs.longlat, side = 3)

    ## Warning in labels.SpatialLines(gl.polar, crs.longlat, side = 3): this labels
    ## method is meant to operate on SpatialLines created with sp::gridlines

    # pos is too simple here, use adj:
    l$pos = NULL
    text(l, adj = c(0.5, -0.3), cex = .8)
    l = labels(gl.polar, crs.longlat, side = 2)

    ## Warning in labels.SpatialLines(gl.polar, crs.longlat, side = 2): this labels
    ## method is meant to operate on SpatialLines created with sp::gridlines

    l$srt = 0 # otherwise they are upside-down
    text(l, cex = .8)
    title("grid line labels on polar projection, epsg 3031")

## Other spatial objects in base plot

The following plot shows polygons with county name as labels at their center point:

    par(mar = c(0, 0, 1, 0))
    plot(nc)
    invisible(text(coordinates(nc), labels=as.character(nc$NAME), cex=0.4))

This plot of a `SpatialPolygonsDataFrame` uses grey shades:

    names(nc)

    ##  [1] "AREA"      "PERIMETER" "CNTY_"     "CNTY_ID"   "NAME"      "FIPS"
    ##  [7] "FIPSNO"    "CRESS_ID"  "BIR74"     "SID74"     "NWBIR74"   "BIR79"
    ## [13] "SID79"     "NWBIR79"

    rrt <- nc$SID74/nc$BIR74
    brks <- quantile(rrt, seq(0,1,1/7))
    cols <- grey((length(brks):2)/length(brks))
    dens <- (2:length(brks))*3
    par(mar = c(0, 0, 1, 0))
    plot(nc, col=cols[findInterval(rrt, brks, all.inside=TRUE)])

The following plot shows a `SpatialPolygonsDataFrame`, using line densities

    rrt <- nc$SID74/nc$BIR74
    brks <- quantile(rrt, seq(0,1,1/7))
    cols <- grey((length(brks):2)/length(brks))
    dens <- (2:length(brks))*3
    par(mar = rep(0,4))
    plot(nc, density=dens[findInterval(rrt, brks, all.inside=TRUE)])

Plot/image of a grid file, using base plot methods:

    image(meuse.grid)

    plot(meuse.grid["dist"])
    points(meuse, col = 'green')

    plot(meuse.grid["dist"], zlim = c(0,1))
    plot(geometry(meuse.grid), add = TRUE, col = grey(.8))

Read this blog post to find out more about the options available (and limitations) for plotting gridded data with base plot methods in sp.

## using lattice plot (spplot)

The following plot colours points with a legend in the plotting area and adds scales:

    spplot(meuse, "zinc", do.log = TRUE,
        key.space=list(x = 0.1, y = 0.95, corner = c(0, 1)),
        scales=list(draw = TRUE))

The following plot has coloured points plot with legend in plotting area and scales; it has a non-default number of cuts with user-supplied legend entries:

    spplot(meuse, "zinc", do.log = TRUE,
        key.space=list(x=0.2,y=0.9,corner=c(0,1)),
        scales=list(draw = TRUE), cuts = 3,
        legendEntries = c("low", "intermediate", "high"))

The following plot adds a scale bar and north arrow:

    scale = list("SpatialPolygonsRescale", layout.scale.bar(),
        offset = c(178600,332490), scale = 500, fill=c("transparent","black"))
    text1 = list("sp.text", c(178600,332590), "0")
    text2 = list("sp.text", c(179100,332590), "500 m")
    arrow = list("SpatialPolygonsRescale", layout.north.arrow(),
        offset = c(178750,332000), scale = 400)
    spplot(meuse, "zinc", do.log=T,
        key.space=list(x=0.1,y=0.93,corner=c(0,1)),
        sp.layout=list(scale,text1,text2,arrow),
        main = "Zinc (top soil)")

The following plot has north arrow and text outside panels

    rv = list("sp.polygons", meuse.riv, fill = "lightblue")
    scale = list("SpatialPolygonsRescale", layout.scale.bar(),
        offset = c(180500,329800), scale = 500, fill=c("transparent","black"), which = 1)
    text1 = list("sp.text", c(180500,329900), "0", which = 1)
    text2 = list("sp.text", c(181000,329900), "500 m", which = 1)
    arrow = list("SpatialPolygonsRescale", layout.north.arrow(),
        offset = c(178750,332500), scale = 400)
    spplot(meuse["zinc"], do.log = TRUE,
        key.space = "bottom",
        sp.layout = list(rv, scale, text1, text2),
        main = "Zinc (top soil)",
        legend = list(right = list(fun = mapLegendGrob(layout.north.arrow()))))

The same plot; north arrow now inside panel, with custom panel function instead of sp.layout

    spplot(meuse, "zinc", panel = function(x, y, ...) {
            sp.polygons(meuse.riv, fill = "lightblue")
            SpatialPolygonsRescale(layout.scale.bar(), offset = c(179900,329600),
                scale = 500, fill=c("transparent","black"))
            sp.text(c(179900,329700), "0")
            sp.text(c(180400,329700), "500 m")
            SpatialPolygonsRescale(layout.north.arrow(),
                offset = c(178750,332500), scale = 400)
            panel.pointsplot(x, y, ...)
        },
        do.log = TRUE, cuts = 7,
        key.space = list(x = 0.1, y = 0.93, corner = c(0,1)),
        main = "Top soil zinc concentration (ppm)")

A multi-panel plot, scales + north arrow only in last plot: using the `which` argument in a layout component (if `which=4` was set as list component of sp.layout, the river would as well be drawn only in that (last) panel)

    rv = list("sp.polygons", meuse.riv, fill = "lightblue")
    scale = list("SpatialPolygonsRescale", layout.scale.bar(),
        offset = c(180500,329800), scale = 500, fill=c("transparent","black"), which = 4)
    text1 = list("sp.text", c(180500,329900), "0", cex = .5, which = 4)
    text2 = list("sp.text", c(181000,329900), "500 m", cex = .5, which = 4)
    arrow = list("SpatialPolygonsRescale", layout.north.arrow(),
        offset = c(181300,329800),
        scale = 400, which = 4)
    cuts = c(.2,.5,1,2,5,10,20,50,100,200,500,1000,2000)
    spplot(meuse, c("cadmium", "copper", "lead", "zinc"), do.log = TRUE,
        key.space = "right", as.table = TRUE,
        sp.layout=list(rv, scale, text1, text2, arrow), # note that rv is up front!
        main = "Heavy metals (top soil), ppm", cex = .7, cuts = cuts)

Comparing four kriging varieties in a multi-panel plot with shared scale:

    rv = list("sp.polygons", meuse.riv, fill = "blue", alpha = 0.1)
    pts = list("sp.points", meuse, pch = 3, col = "grey", alpha = .5)
    text1 = list("sp.text", c(180500,329900), "0", cex = .5, which = 4)
    text2 = list("sp.text", c(181000,329900), "500 m", cex = .5, which = 4)
    scale = list("SpatialPolygonsRescale", layout.scale.bar(),
        offset = c(180500,329800), scale = 500, fill=c("transparent","black"), which = 4)
    library(gstat)
    v.ok = variogram(log(zinc)~1, meuse)
    ok.model = fit.variogram(v.ok, vgm(1, "Exp", 500, 1))
    # plot(v.ok, ok.model, main = "ordinary kriging")
    v.uk = variogram(log(zinc)~sqrt(dist), meuse)
    uk.model = fit.variogram(v.uk, vgm(1, "Exp", 300, 1))
    # plot(v.uk, uk.model, main = "universal kriging")
    meuse[["ff"]] = factor(meuse[["ffreq"]])
    meuse.grid[["ff"]] = factor(meuse.grid[["ffreq"]])
    v.sk = variogram(log(zinc)~ff, meuse)
    sk.model = fit.variogram(v.sk, vgm(1, "Exp", 300, 1))
    # plot(v.sk, sk.model, main = "stratified kriging")
    zn.ok = krige(log(zinc)~1,          meuse, meuse.grid, model = ok.model, debug.level = 0)
    zn.uk = krige(log(zinc)~sqrt(dist), meuse, meuse.grid, model = uk.model, debug.level = 0)
    zn.sk = krige(log(zinc)~ff,         meuse, meuse.grid, model = sk.model, debug.level = 0)
    zn.id = krige(log(zinc)~1,          meuse, meuse.grid, debug.level = 0)

    zn = zn.ok
    zn[["a"]] = zn.ok[["var1.pred"]]
    zn[["b"]] = zn.uk[["var1.pred"]]
    zn[["c"]] = zn.sk[["var1.pred"]]
    zn[["d"]] = zn.id[["var1.pred"]]
    spplot(zn, c("a", "b", "c", "d"),
        names.attr = c("ordinary kriging", "universal kriging with dist to river",
            "stratified kriging with flood freq", "inverse distance"),
        as.table = TRUE, main = "log-zinc interpolation",
        sp.layout = list(rv, scale, text1, text2)
    )

Reuse these results; universal kriging standard errors; grid plot with point locations and polygon (river):

    rv = list("sp.polygons", meuse.riv, fill = "blue", alpha = 0.1)
    pts = list("sp.points", meuse, pch = 3, col = "grey", alpha = .7)
    spplot(zn.uk, "var1.pred",
        sp.layout = list(rv, scale, text1, text2, pts),
        main = "log(zinc); universal kriging using sqrt(dist to Meuse)")

    zn.uk[["se"]] = sqrt(zn.uk[["var1.var"]])
    spplot(zn.uk, "se", sp.layout = list(rv, pts),
        main = "log(zinc); universal kriging standard errors")

    arrow = list("SpatialPolygonsRescale", layout.north.arrow(),
        offset = c(-76,34), scale = 0.5, which = 2)
    spplot(nc, c("SID74", "SID79"), names.attr = c("1974","1979"),
        colorkey=list(space="bottom"), scales = list(draw = TRUE),
        main = "SIDS (sudden infant death syndrome) in North Carolina",
        sp.layout = list(arrow), as.table = TRUE)

    arrow = list("SpatialPolygonsRescale", layout.north.arrow(),
        offset = c(-76,34), scale = 0.5, which = 2)
    #scale = list("SpatialPolygonsRescale", layout.scale.bar(),
    #   offset = c(-77.5,34), scale = 1, fill=c("transparent","black"), which = 2)
    #text1 = list("sp.text", c(-77.5,34.15), "0", which = 2)
    #text2 = list("sp.text", c(-76.5,34.15), "1 degree", which = 2)
    # create a fake lines data set:
    ## multi-panel plot with coloured lines: North Carolina SIDS
    spplot(nc, c("SID74","SID79"), names.attr = c("1974","1979"),
        colorkey=list(space="bottom"),
        main = "SIDS (sudden infant death syndrome) in North Carolina",
        sp.layout = arrow, as.table = TRUE)

Bubble plots for cadmium and zinc:

    b1 = bubble(meuse, "cadmium", maxsize = 1.5, main = "cadmium concentrations (ppm)",
        key.entries = 2^(-1:4))
    b2 = bubble(meuse, "zinc", maxsize = 1.5, main = "zinc concentrations (ppm)",
        key.entries =  100 * 2^(0:4))
    print(b1, split = c(1,1,2,1), more = TRUE)
    print(b2, split = c(2,1,2,1), more = FALSE)

Factor variables using `spplot`:

    # create two dummy factor variables, with equal labels:
    set.seed(31)
    nc$f = factor(sample(1:5, 100,replace = TRUE),labels=letters[1:5])
    nc$g = factor(sample(1:5, 100,replace = TRUE),labels=letters[1:5])
    library(RColorBrewer)
    ## Two (dummy) factor variables shown with qualitative colour ramp; degrees in axes
    spplot(nc, c("f","g"), col.regions=brewer.pal(5, "Set3"), scales=list(draw = TRUE))

## maps using ggplot2

(it is recommended to migrate to `sf`, and use `geom_sf()` for this)

## Interactive maps: leaflet, mapview

R packages leaflet and mapview provide interactive, browser-based maps building upon the leaflet javascript library. Example with points, grid and polygons follow:

    library(mapview)
    mapview(meuse, zcol = c("zinc", "lead"), legend = TRUE)

    mapview(meuse.grid, zcol = c("soil", "dist"), legend = TRUE)

    mapview(nc, zcol = c("SID74", "SID79"), alpha.regions = 1.0, legend = TRUE)

Mapview also allows grids of view that are synced

    m1 <- mapview(meuse, zcol = "soil", burst = TRUE, legend = TRUE)
    m2 <- mapview(meuse, zcol = "lead", legend = TRUE)
    m3 <- mapview(meuse, zcol = "landuse", map.types = "Esri.WorldImagery", legend = TRUE)
    m4 <- mapview(meuse, zcol = "dist.m", legend = TRUE)
    sync(m1, m2, m3, m4) # 4 panels synchronised
    # latticeView(m1, m2, m3, m4) # 4 panels

more examples are found here.

## SessionInfo

    sessionInfo()

    ## R version 4.4.2 (2024-10-31)
    ## Platform: x86_64-pc-linux-gnu
    ## Running under: Ubuntu 24.04.1 LTS
    ##
    ## Matrix products: default
    ## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
    ## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.26.so;  LAPACK version 3.12.0
    ##
    ## locale:
    ##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
    ##  [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=C
    ##  [5] LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_US.UTF-8
    ##  [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C
    ##  [9] LC_ADDRESS=C               LC_TELEPHONE=C
    ## [11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C
    ##
    ## time zone: Europe/Berlin
    ## tzcode source: system (glibc)
    ##
    ## attached base packages:
    ## [1] stats     graphics  grDevices utils     datasets  methods   base
    ##
    ## other attached packages:
    ## [1] mapview_2.11.2     RColorBrewer_1.1-3 gstat_2.1-2        maps_3.4.2.1
    ## [5] sf_1.0-20          raster_3.6-30      sp_2.2-0
    ##
    ## loaded via a namespace (and not attached):
    ##  [1] sass_0.4.9              class_7.3-23            KernSmooth_2.23-26
    ##  [4] lattice_0.22-6          digest_0.6.37           magrittr_2.0.3
    ##  [7] evaluate_1.0.1          grid_4.4.2              fastmap_1.2.0
    ## [10] jsonlite_1.8.9          e1071_1.7-16            DBI_1.2.3
    ## [13] crosstalk_1.2.1         scales_1.3.0            brew_1.0-10
    ## [16] codetools_0.2-20        jquerylib_0.1.4         cli_3.6.3
    ## [19] rlang_1.1.4             leafpop_0.1.0           units_0.8-6
    ## [22] munsell_0.5.1           intervals_0.15.5        base64enc_0.1-3
    ## [25] cachem_1.1.0            yaml_2.3.10             FNN_1.1.4.1
    ## [28] tools_4.4.2             uuid_1.2-1              colorspace_2.1-1
    ## [31] spacetime_1.3-2         R6_2.5.1                png_0.1-8
    ## [34] stats4_4.4.2            zoo_1.8-12              proxy_0.4-27
    ## [37] lifecycle_1.0.4         classInt_0.4-11         leaflet_2.2.2
    ## [40] leaflet.providers_2.0.0 htmlwidgets_1.6.4       terra_1.8-5
    ## [43] bslib_0.8.0             glue_1.8.0              Rcpp_1.0.13-1
    ## [46] systemfonts_1.1.0       xfun_0.50               knitr_1.49
    ## [49] farver_2.1.2            htmltools_0.5.8.1       svglite_2.1.3
    ## [52] rmarkdown_2.29          leafem_0.2.3            xts_0.14.1
    ## [55] satellite_1.0.5         compiler_4.4.2