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Plot variance cubes

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

Plots a variance cube, useful to understand how local smoothing will work.

Usage

# S3 method for class 'variance_cube'
plot(
  x,
  ...,
  tile = x[["tile"]][[1L]],
  roi = NULL,
  labels = NULL,
  palette = "YlGnBu",
  rev = FALSE,
  type = "map",
  quantile = 0.75,
  scale = 1,
  max_cog_size = 1024L,
  legend_position = "inside",
  legend_title = "logvar"
)

Arguments

x

Object of class "variance_cube".

...

Further specifications for plot.

tile

Tile to be plotted.

roi

Spatial extent to plot (see notes)

labels

Labels to plot.

palette

RColorBrewer or "cols4all" palette

rev

Reverse order of colors in palette?

type

Type of plot ("map" or "hist")

quantile

Minimum quantile to plot

scale

Scale to plot map (0.4 to 1.0)

max_cog_size

Maximum size of COG overviews (lines or columns)

legend_position

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

legend_title

Title of legend (default = "probs")

Value

A plot containing local variances associated to the logit probability for each pixel and each class.

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()) {
    # 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()
    )
    # obtain a variance cube
    var_cube <- sits_variance(probs_cube, output_dir = tempdir())
    # plot the variance cube
    plot(var_cube)
}