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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

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

# show landscape and point of interest
show_landscape(classified_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(classified_landscape, new_point, 10, 50)


# show multiple points share
new_points = matrix(c(75, 110, 75, 30), ncol = 2)
show_shareplot(classified_landscape, new_points, 10, 50)


# irregular buffer widths
new_points = matrix(c(75, 110, 75, 30), ncol = 2)
show_shareplot(classified_landscape, new_points, c(10, 30, 50))


# get data frame with results back
result <- show_shareplot(classified_landscape, new_points, 10, 50, return_df = TRUE)
result$share_df
#> # A tibble: 30 × 4
#>    id          layer  freq buffer
#>    <chr>       <fct> <int>  <dbl>
#>  1 Point ID: 1 1        80     10
#>  2 Point ID: 2 1        38     10
#>  3 Point ID: 1 2       236     10
#>  4 Point ID: 2 2       266     10
#>  5 Point ID: 1 3         0     10
#>  6 Point ID: 2 3        12     10
#>  7 Point ID: 1 1       292     20
#>  8 Point ID: 2 1       184     20
#>  9 Point ID: 1 2       964     20
#> 10 Point ID: 2 2      1006     20
#> # ℹ 20 more rows

# use the output from util_extract_multibuffer
new_points = matrix(c(75, 110, 75, 30), ncol = 2)
df = util_extract_multibuffer(classified_landscape, new_points, 10, 50)
show_shareplot(multibuffer_df = df)