.sits_plot_twdtw_class

dtwSatS4 matches objects produced by sits_TWDTW_matches.

matches

Start date of the plot (used for classifications).

start_date

End date of the plot (used for classifications).

end_date

interval

Minimum overlapping between one match
and the interval of classification.
For details see dtwSat::twdtwApply help.

overlap

Plots the results of TWDTW classification (uses dtwSat).

internal

A set of tools for working with satellite image time series, both as individual data or as part of data cubes.
Builds data cubes from collections in AWS, Brazil Data Cube, and Digital Earth Africa.
Provides different visualisation methods for image time series.
Provides smoothing methods for noisy time series.
Includes functions for smoothing based on Bayesian inference.
Enables different clustering methods, including dendrograms and self-organized maps (SOM).
Matches noiseless patterns with noisy time series using the time-weighted dynamic time warping (TWDTW) method for shape recognition.
Provides machine learning methods for time series classification, including support vector machines (SVM), random forests and deep learning.
Minimum recommended requirements: 8 GB RAM and 1 CPU dual-core.

Gilberto Camara

.sits_plot_twdtw_class: Plot classification results using the dtwSat package

Description

Usage

Arguments