Classical Seasonal Decomposition by Moving Averages
Decompose a time series into seasonal, trend and irregular components using moving averages. Deals with additive or multiplicative seasonal component.
Breaks For Additive Season and Trend (BFAST)
BFAST, Breaks For Additive Season and Trend, (Verbesselt et. al) integrates the decomposition of time series into trend, season, and remainder components with methods for detecting and characterizing change within time series.
- Verbesselt, J., Hyndman, R., Newnham, G., & Culvenor, D. (2010). Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment, 114, 106-115. DOI: 10.1016/j.rse.2009.08.014
- Verbesselt, J., Hyndman, R., Zeileis, A., & Culvenor, D. (2010). Phenological change detection while accounting for abrupt and gradual trends in satellite image time series. Remote Sensing of Environment, 114, 2970-2980. DOI: 10.1016/j.rse.2010.08.003.
greenbrown (Forkel et. al) is a collection of functions to analyse trends and trend changes in gridded time series like from satellite observations or climate model simulations. "Greening" describes in the earth observation community positive trends in vegetation greenness.
- Forkel, M., N. Carvalhais, J. Verbesselt, M. Mahecha, C. Neigh and M. Reichstein (2013): Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology. - Remote Sensing 5, 2113-2144.
TIMESAT (Jönsson and Eklundh) is able to investigate the seasonality of satellite time-series data and their relationship with dynamic properties of vegetation, such as phenology and temporal development. TIMESAT is freely available for non-commercial academic research (see distribution policy).
- Jönsson, P. and Eklundh, L. (2002). Seasonality extraction by function fitting to time-series of satellite sensor data. IEEE Transactions on Geoscience and Remote Sensing 40 (8), 1824-1832.
- Jönsson, P. and Eklundh, L. (2004). TIMESAT - a program for analysing time-series of satellite sensor data, Computers and Geosciences 30, 833-845.