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 variance cube

Usage

## S3 method for class 'variance_cube'
plot(
  x,
  ...,
  tile = x[["tile"]][[1]],
  roi = NULL,
  labels = NULL,
  palette = "YlGnBu",
  rev = FALSE,
  type = "map",
  quantile = 0.75,
  scale = 1,
  max_cog_size = 1024,
  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 in WGS 84 - named vector with either (lon_min, lon_max, lat_min, lat_max) or (xmin, xmax, ymin, ymax)
labels	Labels to plot.
palette	RColorBrewer 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.

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()
    )
    # 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 Feb. 13, 2025, 2:22 a.m.