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
)
# segment the image
segments <- sits_segment(
cube = cube,
seg_fn = sits_slic(step = 5,
compactness = 1,
dist_fun = "euclidean",
avg_fun = "median",
iter = 20,
minarea = 10,
verbose = FALSE),
output_dir = tempdir()
)
# classify a data cube
probs_vector_cube <- sits_classify(
data = segments,
ml_model = rfor_model,
output_dir = tempdir()
)
# measure uncertainty
uncert_vector_cube <- sits_uncertainty(
cube = probs_vector_cube,
type = "margin",
output_dir = tempdir()
)
# plot the resulting uncertainty cube
plot(uncert_vector_cube)
}
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