sits_cluster_dendro: Find clusters in time series samples

In e-sensing/sits: Satellite Image Time Series Analysis for Earth Observation Data Cubes

Find clusters in time series samples

Description

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.

Usage

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

## S3 method for class 'sits'
sits_cluster_dendro(
  samples,
  bands = NULL,
  dist_method = "dtw_basic",
  linkage = "ward.D2",
  k = NULL,
  palette = "RdYlGn",
  ...
)

## S3 method for class 'tbl_df'
sits_cluster_dendro(samples, ...)

## Default S3 method:
sits_cluster_dendro(samples, ...)

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.

Value

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.

Author(s)

Rolf Simoes, [e-mail]

References

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

Examples

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

e-sensing/sits documentation built on Jan. 28, 2024, 6:05 a.m.