R/buffer_dist.R

In RFmerge: Merging of Satellite Datasets with Ground Observations using Random Forests

# All the code of this function was taken from the function 'buffer.dist.R' in package GSIF (https://cran.r-project.org/package=GSIF); developed by Tomislav Hengl, Bas Kempen and Gerard Heuvelink with license GPL>=2; and then slighly modified.
# This was the only function needed form that pacakge, adn it was copied into the 'rfmerge' pacakge just to avoid all the dependencies required to install GSIF package
# 

.buffer_dist <- function(observations, predictionDomain, classes, width, ...){

  if(missing(width)){ width <- sqrt(areaSpatialGrid(predictionDomain)) }
  if(!length(classes)==length(observations)){ stop("Length of 'observations' and 'classes' does not match.") }

  ## remove classes without any points:
  xg = summary(classes, maxsum=length(levels(classes)))
  selg.levs = attr(xg, "names")[xg > 0]
  if(length(selg.levs)<length(levels(classes))){
    fclasses <- as.factor(classes)
    fclasses[which(!fclasses %in% selg.levs)] <- NA
    classes <- droplevels(fclasses)
  }

  ## derive buffer distances
  s <- list(NULL)
  for(i in 1:length(levels(classes))){
    s[[i]] <- raster::distance(raster::rasterize(observations[which(classes==levels(classes)[i]),1]@coords, y=raster::raster(predictionDomain)), width=width, ...)
  }

  s <- s[sapply(s, function(x){!is.null(x)})]
  s <- raster::brick(s)
  s <- as(s, "SpatialPixelsDataFrame")
  s <- s[predictionDomain@grid.index,]

  return(s)

} # '.buffer_dist' END