imageRy

Manipulate and share raster images in R. Original code by Duccio Rocchini, Ludovico Chieffallo, Giovanni Andrea Nocera, Giacomo Panza, Michele Torresani and Elisa Thouverai.

Rapid manual available!

Note Rapid manual here

Packages needed

Warning Packages needed to properly run imageRY:

• library(terra)

Ongoing

Import vector s in the CRAN version from Zenodo

im.import()

horizontal and vertical coloring in im.ridgeline() (optional)

R code click here

#' Generate Ridgeline Plots from Satellite Raster Data
#'
#' This function generates ridgeline plots from stacked satellite imagery data.
#'
#' @param im A `SpatRaster` object representing the raster data to be visualized.
#' @param scale A numeric value that defines the vertical scale of the ridgeline plot.
#' @param palette A character string specifying the `viridis` color palette option to use.
#' Available options: `"viridis"`, `"magma"`, `"plasma"`, `"inferno"`, `"cividis"`, `"mako"`, `"rocket"`, `"turbo"`.
#'
#' @return A `ggplot` object displaying the ridgeline plot.
#'
#' @details
#' Ridgeline plots are useful for analyzing temporal variations in raster-based satellite imagery.
#' This function extracts raster values and visualizes their distribution across layers.
#'
#' @references
#' See also `im.import()`, `im.ggplot()`.
#'
#' @seealso [GitHub Repository](https://github.com/ducciorocchini/imageRy/)
#'
#' @examples
#' library(terra)
#' library(ggridges)
#' library(ggplot2)
#'
#' # Create a 5-layer raster
#' r <- rast(nrows = 10, ncols = 10, nlyrs = 5)
#' values(r) <- runif(ncell(r) * 5)
#'
#' # Generate ridgeline plot
#' im.ridgeline(r, scale = 2, palette = "viridis") + theme_minimal()
#' @export
im.ridgeline22 <- function(im, scale, dir = c("h", "v"), palette = c("viridis", "magma", "plasma", "inferno", "cividis", "mako", "rocket", "turbo")) {
  
  palette <- palette[1]
  
  #Checking inputs
  if(!is(im, "SpatRaster")) stop("im must be a SpatRaster")
  if(!is.numeric(scale)) stop("scale must be numeric")
  if(!is.character(palette)) stop("palette must be a character")
  if(!palette %in% c("viridis", "magma", "plasma", "inferno", "cividis", "mako", "rocket", "turbo")) stop("palette must be one of the color options in the viridis package (viridis, magma, plasma, inferno, cividis, mako, rocket, turbo)")
  if(!dir %in% c("h", "v")) stop("dir must be horizontal (h) or vertical (v)")
  
  switch(palette, 
         viridis = 'D',
         magma = 'A',
         inferno = 'B',
         plasma = 'C',
         cividis = 'E',
         rocket = 'F',
         mako = 'G',
         turbo = 'H')
  
  #Transforming im in a dataframe
  df <- as.data.frame(im, wide = FALSE)
  
  #Final graph
  if(dir == "h") {
    pl <- ggplot2::ggplot(df, ggplot2::aes(x = values, y = layer, fill = after_stat(x))) +
      ggridges::geom_density_ridges_gradient(scale = scale, rel_min_height = 0.01) +
      ggplot2::scale_fill_viridis_c(option = palette)
  } else {
    pl <- ggplot2::ggplot(df, ggplot2::aes(x = values, y = layer, fill = after_stat(y))) +
      ggridges::geom_density_ridges_gradient(scale = scale, rel_min_height = 0.01) +
      ggplot2::scale_fill_viridis_c(option = palette)
  }
  
  return(pl)
 
}

Fuzzy classification

im.fuzzyclass()

Avoid alphabetical order and use elements

im.ridgeline()

In PCA, retain the whole set

im.pca()

im.flip()

im.flip <- function(a){
a = flip(a)
plot(a)
return(a)
}

im.export()

im.ggplpotRGB()

im.ggplot() # insert different color ramp palettes

Secretized link:

https://anonymous.4open.science/r/imageRy-5083/README.md

Ongoing in the CRAN version

• insert import vignette
• im.list() to list data from Zenodo
• im.import() to import several layers
• im.classify(): check output