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This article shows how to plot the SpatRaster produced by rasterpic_img() with several packages.

Base plots

The most straightforward option is to use the base plot() methods provided by the package terra (terra::plotRGB()):

library(rasterpic)
library(terra)

# The flag of the United Kingdom
img <- system.file("img/UK_flag.png",
  package = "rasterpic"
)

uk <- sf::st_read(
  system.file("gpkg/UK.gpkg",
    package = "rasterpic"
  ),
  quiet = TRUE
)

uk_img <- rasterpic_img(uk, img, mask = TRUE, inverse = TRUE)
plotRGB(uk_img)

Example: plot with terra package

With ggplot2 + tidyterra

tidyterra provides full support for terra SpatRaster objects:

Example: plot with tidyterra package

With tmap

tmap can be also used to create great maps:

Example: plot with tmap package

With mapsf

mapsf also provides this functionality:

library(mapsf)

mf_raster(uk_img)
mf_scale()
mf_inset_on(x = "worldmap", pos = "topright")
mf_worldmap(uk)
mf_inset_off()

Example: plot with mapsf package

With maptiles

maptiles is a interesting package that provides the ability of downloading map tiles from different providers. It also has a specific function for plotting terra SpatRaster objects:

library(maptiles)

other_tile <- get_tiles(uk, crop = TRUE, zoom = 6)

other_tile_crop <- terra::crop(other_tile, uk_img)

plot_tiles(other_tile_crop)
plot_tiles(uk_img, add = TRUE)

Example: plot with maptiles package

References

Tennekes M (2018). “tmap: Thematic Maps in R.” Journal of Statistical Software, 84(6), 1–39. doi:10.18637/jss.v084.i06.

Giraud T (2024). mapsf: Thematic Cartography. R package version 0.12.0, https://riatelab.github.io/mapsf/.

Hernangómez D (2023). “Using the tidyverse with terra objects: the tidyterra package.” Journal of Open Source Software, 8(91), 5751. ISSN 2475-9066, doi:10.21105/joss.05751, https://doi.org/10.21105/joss.05751.

Hijmans R (2025). terra: Spatial Data Analysis. R package version 1.8-15, https://rspatial.github.io/terra/, https://rspatial.org/.

Wickham H (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.

Session info

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