simts: Simulated seasonal 16-day NDVI time series

In bfast: Breaks For Additive Season and Trend

Description

simts is an object of class "stl" and consists of seasonal, trend (equal to 0) and noise components. The simulated noise is typical for remotely sensed satellite data.

Usage

data(simts)

Source

Verbesselt, J., R. Hyndman, G. Newnham, and D. Culvenor (2009). Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment. http://dx.doi.org/10.1016/j.rse.2009.08.014. Or see http://robjhyndman.com/papers/bfast1.

Examples

plot(simts)
# References
citation("bfast")

Example output

To cite bfast in publications use

  Jan Verbesselt, Rob Hyndman, Glenn Newnham, Darius Culvenor (2010).
  Detecting Trend and Seasonal Changes in Satellite Image Time Series.
  Remote Sensing of Environment, 114(1), 106-115.
  doi:10.1016/j.rse.2009.08.014

  Jan Verbesselt, Rob Hyndman, Achim Zeileis, Darius Culvenor (2010).
  Phenological Change Detection while Accounting for Abrupt and Gradual
  Trends in Satellite Image Time Series. Remote Sensing of Environment,
  114(12), 2970 - 2980. doi:10.1016/j.rse.2010.08.003

If you use bfastmonitor() or bfastpp(), please cite:

  Jan Verbesselt, Achim Zeileis, Martin Herold (2011). Near Real-Time
  Disturbance Detection in Terrestrial Ecosystems Using Satellite Image
  Time Series: Drought Detection in Somalia. Working Paper 2011-18.
  Working Papers in Economics and Statistics, Research Platform
  Empirical and Experimental Economics, Universitaet Innsbruck. URL
  http://EconPapers.RePEc.org/RePEc:inn:wpaper:2011-18

To see these entries in BibTeX format, use 'print(<citation>,
bibtex=TRUE)', 'toBibtex(.)', or set
'options(citation.bibtex.max=999)'.

bfast documentation built on May 2, 2019, 6:53 p.m.