spatialEco (version 1.3-2)

smooth.time.series: Smooth Raster Time-series

Description

Smooths pixel-level data in raster time-series and can impute missing (NA) values.

Usage

smooth.time.series(x, f = 0.8, smooth.data = FALSE, ...)

Arguments

x

A raster stack/brick or sp object with a @data slot

f

Smoothing parameter (see loess span argument)

smooth.data

(FALSE/TRUE) Smooth all of the data or just impute NA values

...

Additional arguments passed to raster calc (for writing results to disk)

Value

A raster stack or brick pr data.frame object with imputed NA values or smoothed data.

Details

This function uses a LOESS regression to smooth the time-series (using the smooth.data = TRUE argument). If the data is smoothed, it will be replaced by a loess estimate of the time-series (estimated distribution at the pixel-level). The results can dramatically be effected by the choice of the smoothing parameter (f) so caution is warranted and the effect of this parameter tested. Alternately, with smooth.data = FALSE, the function can be used to impute missing pixel data (NA) in raster time-series (stacks/bricks).

See Also

loess for details on the loess regression

calc for details on additional (...) arguments

Examples

# NOT RUN {
 random.raster <- function(r=50, c=50, l=10, min=0, max=1){ 
   do.call(stack, replicate(l, raster(matrix(runif(r*c, min, max),r,c))))
 }
 r <- random.raster()

 # Smooth time-series 
 r.smooth <- smooth.time.series(r, f = 0.2, smooth.data = TRUE)  
 
 # sp SpatialPixelsDataFrame example
 r <- as(r, "SpatialPixelsDataFrame")
 r@data <- smooth.time.series(r, f = 0.2, smooth.data = TRUE)
 r <- stack(r) # coerce back to raster stack object

# }