show_landscape

Plot a Raster* object with the NLMR default theme (as ggplot).

show_landscape(x, xlab, ylab, discrete, unique_scales, n_col, n_row, ...)

# S3 method for RasterLayer
show_landscape(x, xlab = "Easting",
  ylab = "Northing", discrete = FALSE, ...)

# S3 method for list
show_landscape(x, xlab = "Easting", ylab = "Northing",
  discrete = FALSE, unique_scales = FALSE, n_col = NULL,
  n_row = NULL, ...)

# S3 method for RasterStack
show_landscape(x, xlab = "Easting",
  ylab = "Northing", discrete = FALSE, unique_scales = FALSE,
  n_col = NULL, n_row = NULL, ...)

# S3 method for RasterBrick
show_landscape(x, xlab = "Easting",
  ylab = "Northing", discrete = FALSE, unique_scales = FALSE,
  n_col = NULL, n_row = NULL, ...)

Arguments

x	Raster* object
xlab	x axis label, default "Easting"
ylab	y axis label, default "Northing"
discrete	If TRUE, the function plots a raster with a discrete legend.
unique_scales	If TRUE and multiple raster are to be visualized, each facet can have a unique color scale for its fill
n_col	If multiple rasters are to be visualized, n_col controls the number of columns for the facet
n_row	If multiple rasters are to be visualized, n_row controls the number of rows for the facet
...	Arguments for theme_nlm

Value

ggplot2 Object

Examples

# \dontrun{
x <- gradient_landscape

# classify
y <- util_classify(gradient_landscape,
                   n = 3,
                   level_names = c("Land Use 1", "Land Use 2", "Land Use 3"))
#> Loading required package: raster
#> Loading required package: sp

show_landscape(x)
show_landscape(y, discrete = TRUE)

show_landscape(list(gradient_landscape, random_landscape))
#> Error: At least one layer must contain all faceting variables: `id`.
#> * Plot is missing `id`
#> * Layer 1 is missing `id`
show_landscape(raster::stack(gradient_landscape, random_landscape))
#> Warning: Removed 598 rows containing missing values (geom_raster).

show_landscape(list(gradient_landscape, y), unique_scales = TRUE)
#> Error: At least one layer must contain all faceting variables: `id`.
#> * Plot is missing `id`
#> * Layer 1 is missing `id`

# }