FillPermanentGaps {greenbrown}R Documentation

Fill permanent gaps in time series

Description

Satellite time series are often affected by permanent gaps like missing observations during winter periods. Often time series methods can not deal with missing observations and require gap-free data. This function fills winter gaps with a constant fill value or according to the approach described in Beck et al. (2006).

Usage

FillPermanentGaps(Yt, min.gapfrac = 0.2, lower = TRUE, fillval = NA, 
    fun = min, ...)

Arguments

Yt

univariate time series of class ts

min.gapfrac

How often has an observation to be NA to be considered as a permanent gap? (fraction of time series length) Example: If the month January is 5 times NA in a 10 year time series (= 0.5), then the month January is considered as permanent gap if min.gapfrac = 0.4.

lower

fill lower gaps (TRUE), upper gaps (FALSE) or lower and upper gaps (NULL)

fillval

constant fill values for gaps. If NA the fill value will be estimated from the data using fun.

fun

function to be used to compute fill values. By default, minimum.

...

further arguments (currently not used)

Value

The function returns a time series with filled permanent gaps.

Author(s)

Matthias Forkel <matthias.forkel@geo.tuwien.ac.at> [aut, cre]

See Also

TsPP

Examples


# load NDVI data
data(ndvi)
plot(ndvi)

# sample some winter months to be set as gaps
winter <- (1:length(ndvi))[cycle(ndvi) == 1 | cycle(ndvi) == 2 | cycle(ndvi) == 12]
gaps <- sample(winter, length(winter)*0.3)

# introduce systematic winter gaps in time series
ndvi2 <- ndvi
ndvi2[gaps] <- NA
plot(ndvi2)
IsPermanentGap(ndvi2)

# fill winter with observed minimum
fill <- FillPermanentGaps(ndvi2)	
plot(fill, col="red"); lines(ndvi)

# fill winter with mean
fill <- FillPermanentGaps(ndvi2, fun=mean)	
plot(fill, col="red"); lines(ndvi)

# fill winter with 0
fill <- FillPermanentGaps(ndvi2, fillval=0)	
plot(fill, col="red"); lines(ndvi)


[Package greenbrown version 2.4.3 Index]