| GetTsStatisticsRaster {greenbrown} | R Documentation |
This function computes statistical properties of the time series in a multi-temporal raster dataset. It calls Decompose to decompose the time series of each grid cell of a raster brick into a trend, inter-annual variability, seasonal and short-term variability time series components. In a next step the mean, the trend slope, the range and standard deviation of the inter-annual variability, the range of the seasonal cycle as well as the range and standard devaition of the short-term variability are calculated.
GetTsStatisticsRaster(r, start = c(1982, 1), freq = 12)
r |
object of class |
start |
first time step, e.g. c(1982, 1) for January 1982. See |
freq |
the number of observations per unit of time, e.g. 12 for monthly data or 24 for bi-monthly data. See |
The function returns a RasterBrick with 7 layers: mean, trend slope, range of inter-annual variabililty, standard deviation of inter-annual variabililty, range of seasonal cycle, range and standard deviation of short-term variabililty.
Matthias Forkel <matthias.forkel@geo.tuwien.ac.at> [aut, cre]
# load a multi-temporal raster dataset of Normalized Difference Vegetation Index data(ndvimap) plot(ndvimap, 8) # calculate time series statistics ndvimap.tsstat <- GetTsStatisticsRaster(ndvimap) plot(ndvimap.tsstat)