sits_som_clean_samples | R Documentation |
sits_som_clean_samples()
evaluates the quality of the samples
based on the results of the SOM map.
sits_som_clean_samples(
som_map,
prior_threshold = 0.6,
posterior_threshold = 0.6,
keep = c("clean", "analyze", "remove")
)
som_map |
Returned by |
prior_threshold |
Threshold of conditional probability (frequency of samples assigned to the same SOM neuron). |
posterior_threshold |
Threshold of posterior probability (influenced by the SOM neighborhood). |
keep |
Which types of evaluation to be maintained in the data. |
tibble with an two additional columns. The first indicates if each sample is clean, should be analyzed or should be removed. The second is the posterior probability of the sample. The "keep" parameter indicates which
The algorithm identifies noisy samples, using 'prior_threshold' for the prior probability and 'posterior_threshold' for the posterior probability. Each sample receives an evaluation tag, according to the following rule: (a) If the prior probability is < 'prior_threshold', the sample is tagged as "remove"; (b) If the prior probability is >= 'prior_threshold' and the posterior probability is >='posterior_threshold', the sample is tagged as "clean"; (c) If the prior probability is >= 'posterior_threshold' and the posterior probability is < 'posterior_threshold', the sample is tagged as "analyze" for further inspection. The user can define which tagged samples will be returned using the "keep" parameter, with the following options: "clean", "analyze", "remove".
Lorena Alves, lorena.santos@inpe.br
Karine Ferreira. karine.ferreira@inpe.br
Gilberto Camara, gilberto.camara@inpe.br
if (sits_run_examples()) {
# create a som map
som_map <- sits_som_map(samples_modis_ndvi)
# plot the som map
plot(som_map)
# evaluate the som map and create clusters
clusters_som <- sits_som_evaluate_cluster(som_map)
# plot the cluster evaluation
plot(clusters_som)
# clean the samples
new_samples <- sits_som_clean_samples(som_map)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.