plot.variance_cube: Plot variance cubes

In e-sensing/sits: Satellite Image Time Series Analysis for Earth Observation Data Cubes

Plot variance cubes

Description

plots a probability cube using stars

Usage

## S3 method for class 'variance_cube'
plot(
  x,
  ...,
  tile = x$tile[[1]],
  labels = NULL,
  palette = "YlGnBu",
  rev = FALSE,
  type = "map",
  tmap_options = NULL
)

Arguments

x	Object of class "variance_cube".
...	Further specifications for plot.
tile	Tile to be plotted.
labels	Labels to plot (optional).
palette	RColorBrewer palette
rev	Reverse order of colors in palette?
type	Type of plot ("map" or "hist")
tmap_options	Named list with optional tmap parameters max_cells (default: 1e+06) scale (default: 1.0) graticules_labels_size (default: 0.7) legend_title_size (default: 1.0) legend_text_size (default: 1.0) legend_bg_color (default: "white") legend_bg_alpha (default: 0.5)

Value

A plot containing probabilities associated to each class for each pixel.

Author(s)

Gilberto Camara, [e-mail]

Examples

if (sits_run_examples()) {
    # create a random forest model
    rfor_model <- sits_train(samples_modis_ndvi, sits_rfor())
    # create a data cube from local files
    data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
    cube <- sits_cube(
        source = "BDC",
        collection = "MOD13Q1-6",
        data_dir = data_dir
    )
    # classify a data cube
    probs_cube <- sits_classify(
        data = cube, ml_model = rfor_model, output_dir = tempdir()
    )
    # obtain a variance cube
    var_cube <- sits_variance(probs_cube, output_dir = tempdir())
    # plot the variance cube
    plot(var_cube)
}

e-sensing/sits documentation built on Jan. 28, 2024, 6:05 a.m.