R: Build a labelled image from a probability cube

sits_label_classification {sits} | R Documentation

## Build a labelled image from a probability cube

### Description

Takes a set of classified raster layers with probabilities, and label them based on the maximum probability for each pixel.

### Usage

    sits_label_classification(
      cube,
      multicores = 2,
      memsize = 4,
      output_dir = ".",
      version = "v1"
    )

### Arguments

`cube` | Classified image data cube.
`multicores` | Number of process to label the classification in snow subprocess.
`memsize` | Maximum overall memory (in GB) to label the classification.
`output_dir` | Output directory where to out the file
`version` | Version of resulting image (in the case of multiple tests)

### Value

A data cube

### Author(s)

Rolf Simoes, rolf.simoes@inpe.br

### Examples

    ## Not run:
    # Retrieve the samples for Mato Grosso
    # select band "ndvi"
    samples_ndvi <- sits_select(samples_modis_4bands, bands = "NDVI")

    # select a random forest model
    rfor_model <- sits_train(samples_ndvi, sits_rfor(num_trees = 500))

    # create a data cube based on the information about the files
    data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
    cube <- sits_cube(
        source = "BDC",
        collection = "MOD13Q1-6",
        data_dir = data_dir,
        delim = "_",
        parse_info = c("X1", "X2", "tile", "band", "date")
    )

    # classify the raster image
    probs_cube <- sits_classify(cube,
        ml_model = rfor_model,
        output_dir = tempdir(),
        memsize = 4, multicores = 2
    )

    # label the classification
    label_cube <- sits_label_classification(probs_cube, output_dir = tempdir())

    ## End(Not run)

[Package sits version 0.16.1 Index]