R/mapSite.R

In track2KBA: Identifying Important Areas from Animal Tracking Data

## mapSite ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

#' Make simple maps of aggregation and important sites
#'
#' \code{mapSite} uses output from \code{findSite} to create maps illustrating
#' density of animals in space, and borders of potentially important areas for
#' the population.
#'
#' If the input is simple features polygons (i.e. \code{polyOut = TRUE} in
#' \code{findSite}), areas which meet threshold of importance are displayed
#' (in red) on top of of the estimated density of animals in space. Black
#' borders are political and coastline borders.If there are no red borders areas
#'  displayed on the map, then either the species doesn't aggregatee enough to
#'  meet the threshold, or the tracked sample aren't representative enough to
#'  identify significant aggregations.
#'
#' If input is SpatialPixelsDataFrame (i.e. \code{polyOut = FALSE} in
#' \code{findSite}), a simple density surface map is plotted.
#'
#' @param Site Simple feature MULTIPOLYGON object or SpatialPixelsDataFrame.
#' Must be output of \code{\link{findSite}} function).
#' @param colony data.frame. Optional. Must contain columns named 'Latitude' and
#'  'Longitude', with coordinate locations to display reference point of, for
#'  example, a breeding or tagging site.
#' @param show logical. show plot, or just save it. Note, saving plot only works
#'  for Simple Features input. Default is TRUE.
#' @return Returns a figure of either single map with all core ranges displayed
#' together, or a series of facetted maps, each of which shows a utilization
#' distribution corresponding to a level of ID in \emph{KDE}.
#'
#' @seealso \code{\link{estSpaceUse}}
#'
#' @examples
#' KDE <- track2KBA::KDE_example
#' 
#' ## identify potential sites
#' pot_site <- findSite(KDE, represent = 90, levelUD = 50)
#' ## Map it
#' mapSite(pot_site)
#' 
#' @export
#' @importFrom sf st_bbox
#' @importFrom ggplot2 geom_sf coord_sf borders ggplot theme element_rect
#' @importFrom ggplot2 ylab xlab scale_fill_continuous scale_colour_continuous
#' @importFrom ggplot2 geom_point guides aes element_line

mapSite <- function(Site, colony=NULL, show=TRUE) {
  if (inherits(Site, "sf")) {

    coordsets <- sf::st_bbox(Site)

    csf <- ggplot2::coord_sf(
      xlim = c(coordsets$xmin, coordsets$xmax),
      ylim = c(coordsets$ymin, coordsets$ymax),
      expand = FALSE
      )
    csf$default <- TRUE

    if (any(Site$N_animals > 1)) {
      label <- "N animals"
    } else {
      label <- "Prop. animals"
    }

    denseplot <- Site %>%
      filter(.data$N_animals > 0) %>%
      ggplot() +
      geom_sf(mapping = aes(
        fill  = .data$N_animals, colour = .data$N_animals)
        ) +
      borders("world", colour = "black", fill = NA) +
      csf +
      scale_fill_continuous(high = "#132B43", low = "#56B1F7", name = label) +
      scale_colour_continuous(high = "#132B43", low = "#56B1F7") +
      theme(panel.background = element_rect(colour = NA, fill = "white"),
        panel.grid.major = element_line(colour = "transparent"),
        panel.grid.minor = element_line(colour = "transparent"),
        panel.border = element_rect(colour = "black", fill = NA, size = 1)) +
      ylab("Latitude") +  xlab("Longitude") + guides(colour = "none")
    # if any areas are potentialSites, add red border
    if (any(Site$potentialSite == TRUE)) {
      potSitearea <- Site %>%
        group_by(.data$potentialSite) %>%
        dplyr::summarise(N_animals = max(.data$N_animals)) %>%
        filter(.data$potentialSite == TRUE)

      denseplot <- denseplot +
        geom_sf(data = potSitearea, colour = "red", fill = NA, size = 1.1) +
        csf
    }
    if (!is.null(colony)) {
      denseplot <- denseplot +
        geom_point(
          data = colony,
          aes(x = .data$Longitude, y = .data$Latitude),
          fill = "dark orange", color = "black", pch = 21, size = 2.5,
          )
      }
    if (show == TRUE) {
      print(denseplot)
    } else { return(denseplot) }

  } else if (inherits(Site,"SpatialPixelsDataFrame")) {
    plot(Site[Site$N_IND > 0, ])
  } else { stop("'Site' is not an sf nor SpatialPixelsDataFrame object") }

}