Title:	Convert Digital Images into 'SpatRaster' Objects
Version:	0.3.0
Description:	Generate 'SpatRaster' objects, as defined by the 'terra' package, from digital images, using a specified spatial object as a geographical reference.
License:	MIT + file LICENSE
URL:	https://dieghernan.github.io/rasterpic/, https://github.com/dieghernan/rasterpic
BugReports:	https://github.com/dieghernan/rasterpic/issues
Depends:	R (≥ 3.6.0)
Imports:	png (≥ 0.1-5), sf (≥ 1.0.0), terra (≥ 1.4-22)
Suggests:	ggplot2, knitr, rmarkdown, testthat (≥ 3.0.0), tidyterra
VignetteBuilder:	knitr
Config/Needs/check:	curl
Config/Needs/coverage:	curl
Config/Needs/website:	dieghernan/gitdevr, tmap, mapsf, maptiles, devtools, curl, remotes, cpp11
Config/testthat/edition:	3
Config/testthat/parallel:	true
Encoding:	UTF-8
RoxygenNote:	7.3.2
X-schema.org-keywords:	cran, jpeg, jpg, maps, png, r, r-package, r-stats, raster, rstats, sf, terra, tif, tiff, cran-r
NeedsCompilation:	no
Packaged:	2025-03-19 17:37:20 UTC; diego
Author:	Diego Hernangómez [aut, cre, cph]
Maintainer:	Diego Hernangómez <diego.hernangomezherrero@gmail.com>
Repository:	CRAN
Date/Publication:	2025-03-19 17:50:02 UTC

rasterpic: Convert Digital Images into 'SpatRaster' Objects

Description

Generate 'SpatRaster' objects, as defined by the 'terra' package, from digital images, using a specified spatial object as a geographical reference.

Author(s)

Maintainer: Diego Hernangómez diego.hernangomezherrero@gmail.com (ORCID) [copyright holder]

See Also

Useful links:

• https://dieghernan.github.io/rasterpic/

• https://github.com/dieghernan/rasterpic

• Report bugs at https://github.com/dieghernan/rasterpic/issues

Compute aspect ratio of an object

Description

Helper function. Ratio is computed as width/height (or col/rows).

Usage

asp_ratio(x)

Arguments

Value

The aspect ratio

Examples

library(terra)

x <- rast(system.file("tiff/elev.tiff", package = "rasterpic"))
plot(x)
asp_ratio(x)

Convert an image to a geo-tagged SpatRaster

Description

Geotags an image based on the coordinates of a given spatial object.

Usage

rasterpic_img(
  x,
  img,
  halign = 0.5,
  valign = 0.5,
  expand = 0,
  crop = FALSE,
  mask = FALSE,
  inverse = FALSE,
  crs = NULL
)

Arguments

Details

vignette("rasterpic", package = "rasterpic") explains with examples the effect of parameters halign, valign, expand, crop and mask.

CRS

The function preserves the Coordinate Reference System of x if applicable. For optimal results do not use geographic coordinates (longitude/latitude).

crs can be in a WKT format, as a "authority:number" code such as "EPSG:4326", or a PROJ-string format such as "+proj=utm +zone=12". It can be also retrieved with:

• sf::st_crs(25830)$wkt.

• terra::crs().

• tidyterra::pull_crs().

See Value and Notes on terra::crs().

Value

A SpatRaster object (see terra::rast()) where each layer corresponds to a color channel of img:

• If img has at least 3 channels (e.g. layers), the result would have an additional property setting the layers 1 to 3 as the Red, Green and Blue channels.

• If img already has a definition or RGB values (this may be the case for tiff/tif files) the result would keep that channel definition.

See Also

From sf:

• sf::st_crs().

• sf::st_bbox().

• vignette("sf1", package = "sf") to understand how sf organizes R objects.

From terra:

• terra::vect(), terra::rast() and terra::ext().

• terra::mask().

• terra::crs().

• terra::RGB().

For plotting:

• terra::plot() and terra::plotRGB().

• With ggplot2 use tidyterra:

  • tidyterra::autoplot.SpatRaster().

  • tidyterra::geom_spatraster_rgb().

Examples

library(sf)
library(terra)
library(ggplot2)
library(tidyterra)


x_path <- system.file("gpkg/UK.gpkg", package = "rasterpic")
x <- st_read(x_path, quiet = TRUE)
img <- system.file("img/vertical.png", package = "rasterpic")

# Default config
ex1 <- rasterpic_img(x, img)

ex1

autoplot(ex1) +
  geom_sf(data = x, fill = NA, color = "white", linewidth = .5)


# Expand
ex2 <- rasterpic_img(x, img, expand = 0.5)

autoplot(ex2) +
  geom_sf(data = x, fill = NA, color = "white", linewidth = .5)


# Align
ex3 <- rasterpic_img(x, img, halign = 0)

autoplot(ex3) +
  geom_sf(data = x, fill = NA, color = "white", linewidth = .5)
labs(title = "Align")

# Crop
ex4 <- rasterpic_img(x, img, crop = TRUE)

autoplot(ex4) +
  geom_sf(data = x, fill = NA, color = "white", linewidth = .5) +
  labs(title = "Crop")

# Mask
ex5 <- rasterpic_img(x, img, mask = TRUE)

autoplot(ex5) +
  geom_sf(data = x, fill = NA, color = "white", linewidth = .5) +
  labs(title = "Mask")

# Mask inverse
ex6 <- rasterpic_img(x, img, mask = TRUE, inverse = TRUE)

autoplot(ex6) +
  geom_sf(data = x, fill = NA, color = "white", linewidth = .5) +
  labs(title = "Mask Inverse")

# Combine Mask inverse and crop
ex7 <- rasterpic_img(x, img, crop = TRUE, mask = TRUE, inverse = TRUE)

autoplot(ex7) +
  geom_sf(data = x, fill = NA, color = "white", linewidth = .5) +
  labs(title = "Combine")

# RGB channels ------
plot(ex1)
ex_rgb <- ex1
has.RGB(ex_rgb)
RGB(ex_rgb)

# Modify RGB channels
RGB(ex_rgb) <- c(2, 3, 1)
RGB(ex_rgb)

plot(ex_rgb)

# Remove RGB channels
RGB(ex_rgb) <- NULL
has.RGB(ex_rgb)
RGB(ex_rgb)

# Note the difference with terra::plot
plot(ex_rgb)