sits_cluster_dendro function

Find clusters in time series samples

These functions support hierarchical agglomerative clustering in sits. They provide support from creating a dendrogram and using it for cleaning samples.

link[sits]{sits_cluster_dendro()} takes a tibble with time series and produces a sits tibble with an added "cluster" column. The function first calculates a dendrogram and obtains a validity index for best clustering using the adjusted Rand Index. After cutting the dendrogram using the chosen validity index, it assigns a cluster to each sample.

link[sits]{sits_cluster_frequency()} computes the contingency table between labels and clusters and produces a matrix. Its input is a tibble produced by link[sits]{sits_cluster_dendro()}.

link[sits]{sits_cluster_clean()} takes a tibble with time series that has an additional cluster produced by link[sits]{sits_cluster_dendro()}

and removes labels that are minority in each cluster.

sits_cluster_dendro(
  samples,
  bands = NULL,
  dist_method = "dtw_basic",
  linkage = "ward.D2",
  k = NULL,
  palette = "RdYlGn",
  ...
)

Arguments

• samples: Tibble with input set of time series (class "sits").
• bands: Bands to be used in the clustering (character vector)
• dist_method: One of the supported distances (single char vector) "dtw": DTW with a Sakoe-Chiba constraint. "dtw2": DTW with L2 norm and Sakoe-Chiba constraint. "dtw_basic": A faster DTW with less functionality. "lbk": Keogh's lower bound for DTW. "lbi": Lemire's lower bound for DTW.
• linkage: Agglomeration method to be used (single char vector) One of "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median" or "centroid".
• k: Desired number of clusters (overrides default value)
• palette: Color palette as per grDevices::hcl.pals() function.
• ...: Additional parameters to be passed to dtwclust::tsclust() function.

Returns

Tibble with "cluster" column (class "sits_cluster").

Note

Please refer to the sits documentation available in https://e-sensing.github.io/sitsbook/ for detailed examples.

Examples

if (sits_run_examples()) {
    # default
    clusters <- sits_cluster_dendro(cerrado_2classes)
    # with parameters
    clusters <- sits_cluster_dendro(cerrado_2classes,
                bands = "NDVI", k = 5)
}

References

"dtwclust" package (https://CRAN.R-project.org/package=dtwclust)

Author(s)

Rolf Simoes, rolf.simoes@inpe.br