sits_sampling_design: 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 allocates a number of sample sizes per strata to obtain suitable values of error-adjusted area, providing five allocation strategies.

Usage

sits_sampling_design(
  cube,
  expected_ua = 0.75,
  alloc_options = c(100, 75, 50),
  std_err = 0.01,
  rare_class_prop = 0.1
)

Arguments

cube	Classified cube
expected_ua	Expected values of user's accuracy
alloc_options	Fixed sample allocation for rare classes
std_err	Standard error we would like to achieve
rare_class_prop	Proportional area limit for rare classes

Value

A matrix with options to decide allocation of sample size to each class. This matrix uses the same format as Table 5 of Olofsson et al.(2014).

Author(s)

Gilberto Camara, [e-mail]

References

[1] Olofsson, P., Foody, G.M., Stehman, S.V., Woodcock, C.E. (2013). Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment, 129, pp.122-131.

[2] Olofsson, P., Foody G.M., Herold M., Stehman, S.V., Woodcock, C.E., Wulder, M.A. (2014) Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148, pp. 42-57.

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()
    )
    # label the probability cube
    label_cube <- sits_label_classification(
        probs_cube,
        output_dir = tempdir()
    )
    # estimated UA for classes
    expected_ua <- c(Cerrado = 0.75, Forest = 0.9,
                     Pasture = 0.8, Soy_Corn = 0.8)
    sampling_design <- sits_sampling_design(label_cube, expected_ua)
}

sits documentation built on Sept. 11, 2024, 6:36 p.m.