Predicts the average spatial distribution of isotopic values over months, years...
This function is the counterpart of isoscape
for the objects
created with isomultifit
. It creates the isoscapes for each
strata (e.g. month) defined by split_by
during the call to
isomultifit
and the aggregate them. The function can handle
weighting for the aggregation process and can thus be used to predict annual
averages precipitation weighted isoscapes.
isomultiscape(raster, isofit, weighting = NULL, verbose = interactive())
raster |
The structural raster (RasterLayer) such as an elevation
raster created using |
isofit |
The fitted isoscape created by |
weighting |
An optional RasterBrick containing the weights |
verbose |
A logical indicating whether information about the progress of the procedure should be displayed or not while the function is running. By default verbose is TRUE if users use an interactive R session and FALSE otherwise. |
This function returns a list of class isoscape containing a set of all 8 raster layers mentioned above (all being of class RasterLayer), and the location of the sources as spatial points.
isoscape
for details on the function used to compute the isoscapes for each strata
isomultifit
for the function fitting the isoscape
plot.ISOSCAPE
for the function plotting the isoscape model
IsoriX
for the complete work-flow
## The examples below will only be run if sufficient time is allowed ## You can change that by typing e.g. options_IsoriX(example_maxtime = XX) ## if you want to allow for examples taking up to ca. XX seconds to run ## (so don't write XX but put a number instead!) if(getOption_IsoriX("example_maxtime") > 180) { ## We prepare the data and split them by month: GNIPDataDEmonthly <- prepsources(data = GNIPDataDE, split_by = "month") dim(GNIPDataDEmonthly) ## We fit the isoscapes:#' GermanMultiFit <- isomultifit(data = GNIPDataDEmonthly, mean_model_fix = list(elev = TRUE, lat.abs = TRUE)) ## We build the annual isoscapes by simple averaging (equal weighting): GermanMultiscape <- isomultiscape(raster = ElevRasterDE, isofit = GermanMultiFit) ## We build the annual isoscapes with a weighing based on precipitation amount: GermanMultiscapeWeighted <- isomultiscape(raster = ElevRasterDE, isofit = GermanMultiFit, weighting = PrecipBrickDE) ## We plot the mean isoscape of the averaging with equal weighting: plot(x = GermanMultiscape, which = "mean") ## We plot the mean isoscape of the averaging with precipitation weighting: plot(x = GermanMultiscapeWeighted, which = "mean") ## We build the isoscapes for a given month (here January): GermanScapeJan <- isoscape(raster = ElevRasterDE, isofit = GermanMultiFit$multi_fits[["month_1"]]) ## We plot the mean isoscape for January: plot(x = GermanScapeJan, which = "mean") }
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