plot.class_cube: Plot classified images

In 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",
  scale = 1,
  max_cog_size = 1024
)

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
scale	Relative scale (0.4 to 1.0) that controls
max_cog_size	Maximum size of COG overviews (lines or columns)

Value

A color map, where each pixel has the color associated to a label, as defined by the legend parameter.

Note

The following optional parameters are available to allow for detailed control over the plot output:

• first_quantile: 1st quantile for stretching images (default = 0.05)

• last_quantile: last quantile for stretching images (default = 0.95)

• graticules_labels_size: size of coordinates labels (default = 0.8)

• legend_title_size: relative size of legend title (default = 1.0)

• legend_text_size: relative size of legend text (default = 1.0)

• legend_bg_color: color of legend background (default = "white")

• legend_bg_alpha: legend opacity (default = 0.5)

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 = "MOD13Q1-6.1",
        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)
}

sits documentation built on Sept. 11, 2024, 6:36 p.m.