sits (version 1.5.3-1)

sits_patterns: Find temporal patterns associated to a set of time series

Description

This function takes a set of time series samples as input estimates a set of patterns. The patterns are calculated using a GAM model. The idea is to use a formula of type y ~ s(x), where x is a temporal reference and y if the value of the signal. For each time, there will be as many predictions as there are sample values. The GAM model predicts a suitable approximation that fits the assumptions of the statistical model, based on a smooth function.

This method is based on the "createPatterns" method of the R dtwSat package, which is also described in the reference paper.

Usage

sits_patterns(data = NULL, freq = 8L, formula = y ~ s(x), ...)

Value

Time series with patterns.

Arguments

data

Time series.

freq

Interval in days for estimates.

formula

Formula to be applied in the estimate.

...

Any additional parameters.

Author

Victor Maus,

Gilberto Camara,

Rolf Simoes,

References

Maus V, Camara G, Cartaxo R, Sanchez A, Ramos F, Queiroz GR. A Time-Weighted Dynamic Time Warping Method for Land-Use and Land-Cover Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 9(8):3729-3739, August 2016. ISSN 1939-1404. tools:::Rd_expr_doi("10.1109/JSTARS.2016.2517118").

Maus, V., Câmara, G., Appel, M., & Pebesma, E. (2019). dtwSat: Time-Weighted Dynamic Time Warping for Satellite Image Time Series Analysis in R. Journal of Statistical Software, 88(5), 1–31. tools:::Rd_expr_doi("10.18637/jss.v088.i05").

Examples

if (sits_run_examples()) {
    patterns <- sits_patterns(cerrado_2classes)
    plot(patterns)
}