R/raster2sample.R

In RRemelgado/fieldRS: Remote Sensing Field Work Tools

#' @title raster2sample
#'
#' @description {Converts a raster grid to points.}
#' @param x Object of class \emph{SpatialPolygons} or \emph{SpatialPolygonDataFrame}.
#' @importFrom raster raster extent crop rasterToPoints rasterize xyFromCell cellFromXY crs
#' @importFrom sp SpatialPointsDataFrame
#' @return A \emph{SpatialPointsDataFrame} with sampled pixels reporting on pixel compactness.
#' @details {\emph{poly2Sample} extends on the \code{\link[raster]{rasterToPoints}} function from the raster package. For 
#' each non-NA pixel in \emph{x}, the function will use 3x3 moving window and report on the frequency of non-NA pixels. 
#' This can be useful to identify "pure" samples within a clump of pixels (i.e. high frequency) as well as mixed pixels 
#' along their borders (i.e. low frequency). The output is a \emph{SpatialPointsDataFrame} reporting on:
#' \itemize{
#'  \item{\emph{x} - x coordinate.}
#'  \item{\emph{y} - y coordinate.}
#'  \item{\emph{cover} - Non-NA value frequency.}
#'  \item{\emph{id} - Corresponding raster value in \emph{x}.}}}
#' @seealso \code{\link{poly2sample}} \code{\link{ccLabel}}
#' @examples {
#'
#'  require(raster)
#'
#'  # load example image
#'  r <- raster(system.file("extdata", "ndvi.tif", package="fieldRS")[1])
#'  r[r < 5000] <- NA
#'  
#'  # extract samples
#'  samples <- raster2sample(r)
#'
#' }
#' @export

#-------------------------------------------------------------------------------------------------------------------------#

raster2sample <- function(x) {
  
#-------------------------------------------------------------------------------------------------------------------------#
# 1. Check input variables
#-------------------------------------------------------------------------------------------------------------------------#
  
  # check/derive reference raster
  if (class(x)[1] != "RasterLayer") {stop('"x" is not a RasterLayer')}
  
#-------------------------------------------------------------------------------------------------------------------------#
# 2. evaluate pixel compactness
#-------------------------------------------------------------------------------------------------------------------------#
  
  px.freq <- focal(x, matrix(1,3,3), function(i) {sum(!is.na(i)) / length(i)})
  
#-------------------------------------------------------------------------------------------------------------------------#
# 3. derive samples
#-------------------------------------------------------------------------------------------------------------------------#
  
  oxy <- xyFromCell(px.freq, which.max(!is.na(x)))
  oxy <- data.frame(x=oxy[,1], y=oxy[,2], cover=extract(px.freq, oxy), id=extract(x, oxy))
  
#-------------------------------------------------------------------------------------------------------------------------#
# 4. build shapefile
#-------------------------------------------------------------------------------------------------------------------------#
  
  return(SpatialPointsDataFrame(oxy[,1:2], oxy, proj4string=crs(x)))
  
}