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Plot Segments

Source: R/sits_plot.R
plot.class_vector_cube.Rd

Plot vector classified cube

Usage

# S3 method for class 'class_vector_cube'
plot(
  x,
  ...,
  tile = x[["tile"]][[1L]],
  legend = NULL,
  roi = NULL,
  seg_color = "black",
  line_width = 0.5,
  palette = "Spectral",
  scale = 1,
  legend_position = "outside"
)

Arguments

x

Object of class "segments".

...

Further specifications for plot.

tile

Tile to be plotted.

legend

Named vector that associates labels to colors.

roi

Region of interest (see note)

seg_color

Segment color.

line_width

Segment line width.

palette

A RColorBrewer or "cols4all" palette

scale

Scale to plot map (0.4 to 1.0)

legend_position

Where to place the legend (default = "outside")

Value

A plot object with an RGB image or a B/W image on a color scale using the chosen palette

Note

To see which color palettes are supported, please run cols4all::c4a_gui().

To define a roi use one of:

  • A path to a shapefile with polygons;

  • A sfc or sf object from sf package;

  • A SpatExtent object from terra package;

  • A named vector ("lon_min", "lat_min", "lon_max", "lat_max") in WGS84;

  • A named vector ("xmin", "xmax", "ymin", "ymax") with XY coordinates.

Author

Gilberto Camara, gilberto.camara@inpe.br

Examples

if (sits_run_examples()) {
    data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
    cube <- sits_cube(
        source = "BDC",
        collection = "MOD13Q1-6.1",
        data_dir = data_dir
    )
    # segment the image
    segments <- sits_segment(
        cube = cube,
        output_dir = tempdir()
    )
    # create a classification model
    rfor_model <- sits_train(samples_modis_ndvi, sits_rfor())
    # classify the segments
    probs_segs <- sits_classify(
        data = segments,
        ml_model = rfor_model,
        output_dir = tempdir()
    )
    #
    # Create a classified vector cube
    class_segs <- sits_label_classification(
        cube = probs_segs,
        output_dir = tempdir(),
        multicores = 2,
        memsize = 4
    )
    # plot the segments
    plot(class_segs)
}