gg.SpatialPolygons: Geom for SpatialPolygons objects

In inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions

Geom for SpatialPolygons objects

Description

Uses the ggplot2::fortify() function to turn the SpatialPolygons objects into a data.frame. Then calls geom_polygon to plot the polygons. Requires the ggplot2 package.

Usage

## S3 method for class 'SpatialPolygons'
gg(data, mapping = NULL, crs = NULL, ...)

Arguments

data	A SpatialPolygons or SpatialPolygonsDataFrame object.
mapping	Aesthetic mappings created by aes used to update the default mapping.
crs	A CRS object defining the coordinate system to project the data to before plotting.
...	Arguments passed on to geom_sf. Unless specified by the user, the argument alpha = 0.2 (alpha level for polygon filling) is added.

Details

Up to version ⁠2.10.0⁠, the ggpolypath package was used to ensure proper plotting, since the ggplot2::geom_polygon function doesn't always handle geometries with holes properly. After ⁠2.10.0⁠, the object is converted to sf format and passed on to gg.sf() instead, as ggplot2 version ⁠3.4.4⁠ deprecated the intenrally used ggplot2::fortify() method for SpatialPolygons/DataFrame objects.

Value

A geom_sf object.

See Also

Other geomes for spatial data: gg(), gg.SpatRaster(), gg.SpatialGridDataFrame(), gg.SpatialLines(), gg.SpatialPixels(), gg.SpatialPixelsDataFrame(), gg.SpatialPoints(), gg.sf()

Examples

  if (require("ggplot2", quietly = TRUE) &&
      requireNamespace("terra", quietly = TRUE) &&
      bru_safe_sp() &&
      require("sp")) {
    # Load Gorilla data

    gorillas <- inlabru::gorillas_sf

    gcov <- gorillas_sf_gcov()
    elev <- terra::as.data.frame(gcov$elevation, xy = TRUE)
    elev <- sf::as_Spatial(sf::st_as_sf(elev, coords = c("x", "y")))

    # Turn elevation covariate into SpatialGridDataFrame
    elev <- sp::SpatialPixelsDataFrame(elev, data = as.data.frame(elev))

    # Plot Gorilla elevation covariate provided as SpatialPixelsDataFrame.
    # The same syntax applies to SpatialGridDataFrame objects.

    ggplot() +
      gg(elev)

    # Add Gorilla survey boundary and nest sightings

    ggplot() +
      gg(elev) +
      gg(gorillas$boundary, alpha = 0.0, col = "red") +
      gg(gorillas$nests)

    # Load pantropical dolphin data

    mexdolphin <- inlabru::mexdolphin_sp()

    # Plot the pantropical survey boundary, ship transects and dolphin sightings

    ggplot() +
      gg(mexdolphin$ppoly) + # survey boundary as SpatialPolygon
      gg(mexdolphin$samplers) + # ship transects as SpatialLines
      gg(mexdolphin$points) # dolphin sightings as SpatialPoints

    # Change color

    ggplot() +
      gg(mexdolphin$ppoly, color = "green") + # survey boundary as SpatialPolygon
      gg(mexdolphin$samplers, color = "red") + # ship transects as SpatialLines
      gg(mexdolphin$points, color = "blue") # dolphin sightings as SpatialPoints


    # Visualize data annotations: line width by segment number

    names(mexdolphin$samplers) # 'seg' holds the segment number
    ggplot() +
      gg(mexdolphin$samplers, aes(color = seg))

    # Visualize data annotations: point size by dolphin group size

    names(mexdolphin$points) # 'size' holds the group size
    ggplot() +
      gg(mexdolphin$points, aes(size = size))
  }

inlabru documentation built on Aug. 9, 2025, 1:08 a.m.