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show_shareplot

Source: R/show_shareplot.R
show_shareplot.Rd

Plot the landscape share in subsequential buffers around a/multiple point(s) of interest

Usage

show_shareplot(
  landscape,
  points,
  buffer_width,
  max_width = NULL,
  multibuffer_df = NULL,
  return_df = FALSE
)

show_shareplot(
  landscape,
  points,
  buffer_width,
  max_width = NULL,
  multibuffer_df = NULL,
  return_df = FALSE
)

Arguments

landscape

Raster* object

points

Point(s) represented by a two-column matrix or data.frame; SpatialPoints*; SpatialPolygons*; SpatialLines; Extent; a numeric vector representing cell numbers; or sf* POINT object

buffer_width

Buffer widths in which landscape share is measured. By default, it is a vector of buffer sizes, if max_width = NULL. If a value if provided for max_width, a series of buffer sizes is created, from buffer_width to max_width, with increases of buffer_width.

max_width

Max distance to which buffer_width is summed up; the x axis in the plot

multibuffer_df

data.frame with landscape share or a function from it already extracted, such as through the util_extract_multibuffer() function. If given, the other arguments (landscape, points, buffer_width, max_width) are ignored. Default is NULL.

return_df

Logical value indicating if a tibble with the underlying data should be returned

Value

ggplot2 Object

Examples

# Minimal runnable example with a pre-built multi-buffer data frame
df <- data.frame(
  id = "Point ID: 1",
  layer = factor(rep(1:3, each = 2)),
  freq = c(10, 15, 20, 25, 5, 10),
  buffer = rep(c(10, 20), 3)
)
show_shareplot(multibuffer_df = df)


# \donttest{
# use a smaller aggregated landscape for the longer-running examples below
small_landscape <- raster::aggregate(classified_landscape, fact = 5)

# create single point
new_point <- matrix(c(75, 75), ncol = 2)

# show landscape and point of interest
show_landscape(small_landscape, discrete = TRUE) +
ggplot2::geom_point(data = data.frame(x = new_point[, 1], y = new_point[, 2]),
                    ggplot2::aes(x = x, y = y),
                    col = "grey", size = 3)


# show single point share
show_shareplot(small_landscape, new_point, 10, 30)


# show multiple points share
new_points <- matrix(c(75, 110, 75, 30), ncol = 2)
show_shareplot(small_landscape, new_points, 10, 30)


# irregular buffer widths
show_shareplot(small_landscape, new_points, c(10, 30))


# get data frame with results back
result <- show_shareplot(small_landscape, new_points, 10, 30, return_df = TRUE)
result$share_df
#> # A tibble: 174 × 4
#>    id          layer  freq buffer
#>    <chr>       <fct> <int>  <dbl>
#>  1 Point ID: 1 1.16      1     10
#>  2 Point ID: 2 1.16      0     10
#>  3 Point ID: 1 1.32      1     10
#>  4 Point ID: 2 1.32      1     10
#>  5 Point ID: 1 1.44      1     10
#>  6 Point ID: 2 1.44      0     10
#>  7 Point ID: 1 1.6       1     10
#>  8 Point ID: 2 1.6       0     10
#>  9 Point ID: 1 1.64      1     10
#> 10 Point ID: 2 1.64      1     10
#> # ℹ 164 more rows

# use the output from util_extract_multibuffer
df <- util_extract_multibuffer(small_landscape, new_points, 10, 30)
show_shareplot(multibuffer_df = df)

# }