plot.class_cube: Plot classified images

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

Plot classified images

Description

plots a classified raster using ggplot.

Usage

## S3 method for class 'class_cube'
plot(
  x,
  y,
  ...,
  tile = x$tile[[1]],
  title = "Classified Image",
  legend = NULL,
  palette = "Spectral",
  tmap_options = NULL
)

Arguments

x	Object of class "class_cube".
y	Ignored.
...	Further specifications for plot.
tile	Tile to be plotted.
title	Title of the plot.
legend	Named vector that associates labels to colors.
palette	Alternative RColorBrewer palette
tmap_options	Named list with optional tmap parameters max_cells (default: 1e+06) scale (default: 0.5) 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 color map, where each pixel has the color associated to a label, as defined by the legend parameter.

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()
    )
    # label cube with the most likely class
    label_cube <- sits_label_classification(
        probs_cube,
        output_dir = tempdir()
    )
    # plot the resulting classified image
    plot(label_cube)
}

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