The writeRast() function exports rasters stored in SpatRaster objects to
GeoTIFF or NetCDF files.
Arguments
- rast
SpatRasterobject.- filename
character. Output file name. Can be either a
".tiff"file (GeoTIFF) or".nc"(NetCDF). By defaultfilename=NULLand the name of the file is generated based on raster information (storms and products) with the '.tiff' extension.- path
character. Path to the directory where the file is exported to. By default
path=./'.- ...
Additional arguments to be passed to
terra::writeRasterfunction when saving to".tiff"format.
Examples
# Creating a stormsDataset
# \donttest{
sds <- defStormsDataset()
#> Warning: No basin argument specified. StormR will work as expected
#> but cannot use basin filtering for speed-up when collecting data
#> === Loading data ===
#> Open database... /home/runner/work/_temp/Library/StormR/extdata/test_dataset.nc opened
#> Collecting data ...
#> === DONE ===
# Getting storm track data for tropical cyclone Pam (2015) near Vanuatu
pam <- defStormsList(sds = sds, loi = "Vanuatu", names = "PAM")
#> === Storms processing ... ===
#>
#> -> Making buffer: Done
#> -> Searching for PAM storm ...
#> -> Identifying Storms: Done
#> -> Gathering storm(s) ...
#>
#> === DONE with run time 0.4782274 sec ===
#>
#> SUMMARY:
#> (*) LOI: Vanuatu
#> (*) Buffer size: 300 km
#> (*) Number of storms: 1
#> Name - Tropical season - Scale - Number of observation within buffer:
#> PAM - 2015 - 6 - 20
#>
# Computing maximum sustained wind speed
pam.msw <- spatialBehaviour(pam)
#> === spatialBehaviour processing ... ===
#>
#> Initializing data ... Done
#>
#> Computation settings:
#> (*) Temporal resolution: Every 60 minutes
#> (*) Space resolution: 2.5min
#> (*) Method used: Willoughby
#> (*) Product(s) to compute: MSW
#> (*) Asymmetry used: Chen
#>
#> Storm(s):
#> ( 1 ) PAM
#>
#> PAM ( 1 / 1 )
#>
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#>
#> === DONE with run time 3.271 sec ===
#>
#> Output:
#> SpatRaster stack with 1 layers:
#> index - name of layers
#> 1 PAM_MSW
#>
# Exporting maximum sustained wind speed raster layer to a GeoTIFF file
writeRast(pam.msw, path = paste0(tempdir(), "/"))
# Computing power dissipation index for several storms near New Caledonia
sts.nc <- defStormsList(sds = sds, loi = "New Caledonia")
#> === Storms processing ... ===
#>
#> -> Making buffer: Done
#> -> Searching storms from 2015 to 2021 ...
#> -> Identifying Storms: 9 potential candidates...
#> -> Gathering storm(s) ...
#>
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#>
#> === DONE with run time 0.576256 sec ===
#>
#> SUMMARY:
#> (*) LOI: New Caledonia
#> (*) Buffer size: 300 km
#> (*) Number of storms: 7
#> Name - Tropical season - Scale - Number of observation within buffer:
#> PAM - 2015 - 6 - 5
#> SOLO - 2015 - 1 - 15
#> ULA - 2016 - 5 - 9
#> UESI - 2020 - 2 - 16
#> GRETEL - 2020 - 2 - 11
#> LUCAS - 2021 - 2 - 16
#> NIRAN - 2021 - 6 - 10
#>
pdi.nc <- spatialBehaviour(sts.nc, product = "PDI")
#> === spatialBehaviour processing ... ===
#>
#> Initializing data ... Done
#>
#> Computation settings:
#> (*) Temporal resolution: Every 60 minutes
#> (*) Space resolution: 2.5min
#> (*) Method used: Willoughby
#> (*) Product(s) to compute: PDI
#> (*) Asymmetry used: Chen
#>
#> Storm(s):
#> ( 7 ) PAM SOLO ULA UESI GRETEL LUCAS NIRAN
#>
#> PAM ( 1 / 7 )
#>
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#> SOLO ( 2 / 7 )
#>
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#> ULA ( 3 / 7 )
#>
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#> UESI ( 4 / 7 )
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#> GRETEL ( 5 / 7 )
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#> LUCAS ( 6 / 7 )
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#> NIRAN ( 7 / 7 )
#>
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#>
#> === DONE with run time 17.428 sec ===
#>
#> Output:
#> SpatRaster stack with 7 layers:
#> index - name of layers
#> 1 PAM_PDI
#> 2 SOLO_PDI
#> 3 ULA_PDI
#> 4 UESI_PDI
#> 5 GRETEL_PDI
#> 6 LUCAS_PDI
#> 7 NIRAN_PDI
#>
# Exporting the power dissipation index raster layers to a NetCDF file
writeRast(pdi.nc, path = paste0(tempdir(), "/"))
# }