sits_stratified_sampling: Allocation of sample size to strata

In sits: Satellite Image Time Series Analysis for Earth Observation Data Cubes

Allocation of sample size to strata

Description

Takes a class cube with different labels and a sampling design with a number of samples per class and allocates a set of locations for each class

Usage

sits_stratified_sampling(
  cube,
  sampling_design,
  alloc = "alloc_prop",
  overhead = 1.2,
  multicores = 2L,
  shp_file = NULL,
  progress = TRUE
)

Arguments

cube	Classified cube
sampling_design	Result of sits_sampling_design
alloc	Allocation method chosen
overhead	Additional percentage to account for border points
multicores	Number of cores that will be used to sample the images in parallel.
shp_file	Name of shapefile to be saved (optional)
progress	Show progress bar? Default is TRUE.

Value

samples Point sf object with required samples

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",
        data_dir = data_dir
    )
    # classify a data cube
    probs_cube <- sits_classify(
        data = cube, ml_model = rfor_model, output_dir = tempdir()
    )
    # label the probability cube
    label_cube <- sits_label_classification(
        probs_cube,
        output_dir = tempdir()
    )
    # estimated UA for classes
    expected_ua <- c(Cerrado = 0.95, Forest = 0.95,
                     Pasture = 0.95, Soy_Corn = 0.95)
    # design sampling
    sampling_design <- sits_sampling_design(label_cube, expected_ua)
    # select samples
    samples <- sits_stratified_sampling(label_cube,
                                        sampling_design, "alloc_prop")

}

sits documentation built on May 29, 2024, 5:55 a.m.