Description Usage Arguments Details Value References Examples
genSmoothingCovIMA
runs the image mean anomaly (IMA) algorithm
with covariates \insertCitemilitino2018improvingRGISTools.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
rStack |
a |
cStack |
a |
Img2Process |
a |
nDays |
a |
nYears |
a |
r.dates |
a |
fact |
a |
fun |
a |
aFilter |
a |
snow.mode |
logical argument. If |
out.name |
the name of the folder containing the filled/smoothed images when saved in the Hard Disk Drive (HDD). |
... |
arguments for nested functions:
|
This filling/smoothing method was developed by \insertCitemilitino2018improving;textualRGISTools. This technique decomposes a time series of images into a new series of mean and anomaly images. The procedure applies the filling/smoothing algorithm with covariates over the anomaly images. The procedure requires a proper definition of a temporal neighbourhood for the target image and aggregation factor.
a RasterStack
with the filled/smoothed images.
militino2018improvingRGISTools
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | ## Not run:
set.seed(0)
# load example ndvi and dem data of Navarre
data(ex.ndvi.navarre)
data(ex.dem.navarre)
# plot example data
genPlotGIS(ex.ndvi.navarre)
genPlotGIS(ex.dem.navarre)
# distorts 5% of the original ndvi data by
# altering 50% its values
for(x in c(2,5)){
aux <- sampleRandom(ex.ndvi.navarre[[x]],
ncell(ex.ndvi.navarre) * 0.05,
cells = TRUE,
na.rm = TRUE)
ex.ndvi.navarre[[x]][aux[,1]] <- aux[,2] * 1.5
}
genPlotGIS(ex.ndvi.navarre)
# smoothing the image using the DEM as covariate
smth.ndvi <- genSmoothingCovIMA(rStack = ex.ndvi.navarre,
cStack = ex.dem.navarre,
Img2Process = c(2))
# plot the distorted 1, smoothed 1,
# distorted 5, smoothed 5 images
plot(stack(ex.ndvi.navarre[[2]],
smth.ndvi[[1]],
ex.ndvi.navarre[[5]],
smth.ndvi[[2]]))
## End(Not run)
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