News: TIMESAT 3.2 with parallel processing is now released (Apr. 27, 2015).
TIMESAT is a software package for analysing time-series of satellite sensor data. We have developed TIMESAT to be able to investigate the seasonality of satellite time-series data and their relationship with dynamic properties of vegetation, such as phenology and temporal development. The temporal domain holds important information about short- and long-term vegetation changes.
TIMESAT was originally intended for handling noisy time-series of AVHRR NDVI data and to extract seasonality information from the data. The program now has the capability to handle different types of remotely sensed time-series , e.g. data from Terra/MODIS at different time resolutions. It has also been tested with eddy covariance data and moisture data, although these applications are not the main target.
Output from the program consists of seasonality parameters (Figure 1), as well as fitted function files containing smooth renditions of the original data.
Figure 1. Some of the seasonality parameters generated in TIMESAT: (a) beginning of season, (b) end of season, (c) length of season, (d) base value, (e) time of middle of season, (f) maximum value, (g) amplitude, (h) small integrated value, (h+i) large integrated value. This figure is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 2.5 Sweden License. It is free to copy and use in other work.
The function fitting is done in steps. In the first step the number of seasons and their approximate timing is defined. The second step filters the data or fits smooth functions to the data (Savitzky-Golay filter, or least-squares fitted assymetric Gaussian or double logistic smooth functions). After the fitting has been achieved, the seasonality parameters are computed and written to output files.
TIMESAT runs from a graphical user interface. For large images or long time-series Fortran executables ensure fast processing. Matlab is the default running environment but is no longer required.
TIMESAT is freely available for non-commercial academic research (see our Distribution policy).