Package 'BNRTools'

Inverse of 'in' call

Description

Calculates the set of entries not present in the second vector. Added for convenience since this is not supported by default in R.

Usage

a %notin% b

Arguments

a	First vector object.
b	Second vector object.

Value

A vector of logical entries of 'a' not present in 'b'.

Author(s)

Martin Jung

Examples

# example code

---

Function to format a prepared GLOBIOM netCDF file for use in ibis.iSDM

Description

This function expects a downscaled GLOBIOM output as created in the BIOCLIMA project. It converts the input to a stars object to be fed to the ibis.iSDM R-package.

Usage

conv_downscalr2ibis(
  fname,
  ignore = NULL,
  period = "all",
  template = NULL,
  shares_to_area = FALSE,
  use_gdalutils = FALSE,
  verbose = TRUE
)

Arguments

fname	A filename in character pointing to a GLOBIOM output in netCDF format.
ignore	A vector of variables to be ignored (Default: NULL).
period	A character limiting the period to be returned from the formatted data. Options include "reference" for the first entry, "projection" for all entries but the first, and "all" for all entries (Default: "reference").
template	An optional SpatRaster object towards which projects should be transformed.
shares_to_area	A logical on whether shares should be corrected to areas (if identified).
use_gdalutils	(Deprecated) logical on to use gdalutils hack-around.
verbose	logical on whether to be chatty.

Value

A SpatRaster stack with the formatted GLOBIOM predictors.

Author(s)

Martin Jung

Examples

## Not run: 
## Does not work unless downscalr file is provided.
# Expects a filename pointing to a netCDF file.
covariates <- conv_downscalr2ibis(fname)

## End(Not run)

---

Check if a directory is empty (and create it if it doesn't exist)

Description

This function checks whether a specified directory is empty. If the directory does not exist, it will be created.

Usage

misc_emptyfolder(dir_path)

Arguments

dir_path

A character string specifying the path to the directory.

Details

It also checks whether the directory is newly created or already existed.

Value

A logical value: TRUE if the directory is empty (or newly created), FALSE otherwise.

Author(s)

Martin Jung

Contributors: ChatGPT

Examples

# Check and create a directory
dir_path <- tempfile()
is_empty <- misc_emptyfolder(dir_path)
print(is_empty)
unlink(dir_path, recursive = TRUE)

---

Shows size of objects in the R environment

Description

Shows the size of the objects currently in the R environment. Helps to locate large objects cluttering the R environment and/or causing memory problems during the execution of large workflows.

Usage

misc_objectSize(n = 10)

Arguments

n	Number of objects to show, Default: 10

Value

A data frame with the row names indicating the object name, the field 'Type' indicating the object type, 'Size' indicating the object size, and the columns 'Length/Rows' and 'Columns' indicating the object dimensions if applicable.

Author(s)

Bias Benito

Examples

if(interactive()){

 #creating dummy objects
 x <- matrix(runif(100), 10, 10)
 y <- matrix(runif(10000), 100, 100)

 #reading their in-memory size
 misc_objectSize()

}

---

Sanitize variable names

Description

Prepared covariates often have special characters in their variable names which can or can not be used in formulas or cause errors for certain procedures. This function converts special characters (points, underscores or similar) of variable names into a species format.

Usage

misc_sanitizeNames(names)

Arguments

names

A vector of character vectors to be sanitized.

Value

A vector of sanitized character.

Examples

# Correct variable names
vars <- c("Climate-temperature2015", "Elevation__sealevel", "Landuse.forest..meanshare")
misc_sanitizeNames(vars)

---

Clip and mask a raster using a raster or vector template

Description

Aligns a SpatRaster or stars raster to a raster template, or clips it to a vector template. Vector geometries are rasterized on the target grid and used as a mask.

Usage

spl_clipMask(x, template, method = c("bilinear", "near"), touches = FALSE)

Arguments

x	A SpatRaster or stars object to clip and mask.
template	A SpatRaster or stars raster template, an sf or sfc object, or a path to a raster or vector file.
method	Resampling method: "bilinear" for continuous data or "near" for categorical data (Default: "bilinear").
touches	If TRUE, rasterize all cells touched by vector geometries; otherwise rasterize cells whose centers fall within them (Default: FALSE).

Value

An object of the same class as x, with its layer count and names preserved. Raster templates set the output grid and, when they contain values, mask cells where the first layer is NA. Vector templates crop the output to their extent and mask it to the rasterized geometry.

Author(s)

Martin Jung

See Also

terra::crop(), terra::extend(), terra::mask(), terra::project(), terra::rasterize(), terra::resample()

Examples

target <- terra::rast(nrows = 10, ncols = 10, xmin = 0, xmax = 10,
                      ymin = 0, ymax = 10, crs = "EPSG:4326", vals = 1:100)
boundary <- sf::st_sf(
  id = 1,
  geometry = sf::st_sfc(sf::st_polygon(list(rbind(
    c(2, 2), c(8, 2), c(8, 8), c(2, 8), c(2, 2)
  ))), crs = 4326)
)
clipped <- spl_clipMask(target, boundary)

---

RExport a gridded raster to a NetCDF format

Description

This function serves as a general wrapper function to export a provided spatial gridded layer as multi-dimensional NetCDF file. It furthermore requires the specification of a list containing metadata information.

Usage

spl_exportNetCDF(
  obj,
  filename,
  global_meta = system.file("iiasa_meta.yaml", package = "BNRTools"),
  separate_meta = FALSE,
  ...
)

Arguments

obj	A SpatRaster object to be exported.
filename	A character with the output filename.
global_meta	A global metadata descriptor by default using IIASA standard metadata (Default: "iiasa_meta data").
separate_meta	A logical flag on whether the metadata should be written separately in "yaml" format (Default: FALSE).
...	Any other metadata that should be overwritten or added to "global_meta".

Details

The default metadata is contained in "inst/iiasa_meta". See examples.

Note

A support for 'stars' could be added.

Author(s)

Martin Jung

See Also

writeCDF, writeRaster

Examples

## Not run: 
# Load default metadata (loaded by default by function too)
meta <- yaml::read_yaml(system.file("iiasa_meta.yaml", package = "BNRTools"))

# Dummy raster
obj <- terra::rast(ncol = 100, nrow = 100,
                   xmin = 0, xmax = 100,
                   ymin = 0, ymax = 100,
                   resolution = 5, crs = terra::crs("WGS84"),
                   val = runif(400)
                   )

# Export
spl_exportNetCDF(obj, filename = "test.nc",
                     global_meta = meta, title = "Super cool analysis")

## End(Not run)

---

Grow a categorical SpatRaster by certain amount of pixels or distance.

Description

A common issue in aggregating categorical rasters is that coastal and boundary gridcells tend to decrease owing to aggregation effects. This can cause issues of non-matching grid cells later on. This simple function takes a categorical SpatRaster object and grows it into no-data areas (those with NA values) within an optionally provided distance.

Usage

spl_growGrid(x, iter = 2)

Arguments

x	A categorical SpatRaster to be grown.
iter	A numeric values of the maximum number of iterations from the grid cell border of which x should be grown (Default: 2).

Value

SpatRaster

Note

Only NA grid cells will be filled!

See Also

buffer, focal

Examples

set.seed(42)
ras <- terra::rast(ncol = 100, nrow = 100, xmin = 0, xmax = 100,
ymin = 0, ymax = 100, resolution = 10, crs = NA)

# Fill with dummy values but keep half as NA
terra::values(ras) <- c(rep(NA,50),rbinom(terra::ncell(ras)/2, 10, 0.5))

# Convert to factor
ras <- terra::as.factor(ras)
assertthat::assert_that(terra::is.factor(ras))

ras_nona <- spl_growGrid(x = ras, iter = 10)
terra::plot(ras_nona)

---

Mosaic a list of spatial layers together.

Description

Particular for large spatial files, it is often impractical to process the entire layer as single file. Instead such a file could be split in smaller chunks and processed as such.

A common issue then is to reconstruct a spatial file of the original extent. This function takes a list of filenames as input and mosaics them together using a 'vrt' file format.

Usage

spl_mosaicTiffs(files, ofname = NULL, tempdir = NULL, dt = "INT2S", ...)

Arguments

files	A character vector with filenames of spatial files.
ofname	A character where the output should be written (Default: NULL).
tempdir	A character with a temporary folder that must exist (Default: NULL).
dt	A character with the output datatype of the spatial file (Default: "INT2S").
...	Any other parameters passed to writeRaster.

Details

This function by default uses the 'gdalUtilities' R-package and tools for most of the projections.

Value

A SpatRaster or just a file.

Author(s)

Martin Jung

See Also

mosaic, gdalbuildvrt

Examples

## Not run: 
 # Get list of files
 ll <- list.files(path_to_folder)

 # Mosaic
 spl_mosaicTiffs(ll, "full_file.tif")

## End(Not run)

---

Replace NA values in gridded layers with a fixed value.

Description

This function replaces all NA values in a spatial gridded layer with a fixed value such as for example 0. Accepted input layers are for SpatRaster from the "terra" R-package and stars from the "stars" R-package.

Usage

spl_replaceGriddedNA(obj, value = 0, mask, verbose = FALSE)

Arguments

obj	A SpatRaster, SpatRasterDataset or stars object.
value	A fixed numeric value of which all NA values are to be replaced with (Default: 0).
mask	An optional SpatRaster object used instead of the value.
verbose	Be chatty about what is processed (Default: FALSE).

Details

Required inputs are a single "obj" gridded data object and a numeric value. In addition an optional mask layer can be provided that to use a mask. In this case all no-data values a replaced with the value in this mask.

Value

A object of the same type as the input but with no-data values replaced with 'value'.

Author(s)

Martin Jung

Examples

# Example
s <- terra::rast(system.file("ex/logo.tif", package="terra"))
s[sample(1:terra::ncell(s), 100)] <- NA
sfill <- spl_replaceGriddedNA(s, value = 100)
terra::plot(sfill)

---

Resample raster

Description

Resample two raster to the spatial resolution using aggregation or disaggregation.

Usage

spl_resampleRas(x, y, discrete = FALSE)

Arguments

x	A SpatRaster to be resampled.
y	A SpatRaster to which x will be resampled
discrete	logical to specifiy if input raster has continitous or discrete values

Value

SpatRaster

See Also

aggregate, disagg

Examples

set.seed(42)
ras_a <- terra::rast(ncol = 100, nrow = 100, xmin = 0, xmax = 100,
ymin = 0, ymax = 100, resolution = 20, crs = NA)

ras_b <- terra::rast(ncol = 100, nrow = 100, xmin = 0, xmax = 100,
ymin = 0, ymax = 100, resolution = 5, crs = NA)

 terra::values(ras_a) <- runif(n = terra::ncell(ras_a))
 terra::values(ras_b) <- runif(n = terra::ncell(ras_b))

 spl_resampleRas(x = ras_a, y = ras_b)

---

Calculates a rarity-weighted richness estimate from modelled species distributions

Description

This function calculates a rarity-weighted richness estimate from modelled species distributions, which can for example be obtained from the `ibis.iSDM` R-package. The input maps should ideally be binary presence-absence maps, but the function can also handle continuous predictions.

Usage

spl_rwr(x, normalize = TRUE, column = NULL)

Arguments

x	A SpatRaster or alternatively data.frame object containing the modelled species distributions.
normalize	A logical flag on whether to normalize the rarity-weighted richness ranks.
column	An optional character value on whether the (Default: NULL).

Details

The function

Value

A logical value: TRUE if the directory is empty (or newly created), FALSE otherwise.

Author(s)

Martin Jung

References

• Albuquerque, F., & Beier, P. (2016). Predicted rarity‐weighted richness, a new tool to prioritize sites for species representation. Ecology and Evolution, 6(22), 8107-8114.

• Albuquerque, F., & Beier, P. (2015). Rarity-weighted richness: a simple and reliable alternative to integer programming and heuristic algorithms for minimum set and maximum coverage problems in conservation planning. PloS one, 10(3), e0119905.

Examples

## Not run: 
# Calculate rarity-weighted richness from a [`SpatRaster`].


## End(Not run)

---

Summarize a set of layers from geopackages

Description

Geopackages are a common format for storing spatial data, allowing multiple layers within a single file. These can be for example point or polygon data.

Usage

spl_summarizeGPKGlayers(folder, verbose = TRUE)

Arguments

folder	A character string specifying the path where the geopackage files are stored. This looks specifically for files with the '.gpkg' extension, skipping others.
verbose	A logical value indicating whether to print additional information during processing.

Value

A data.frame summarizing the layers in the geopackage, including their names, geometry types, and feature counts.

Author(s)

Martin Jung

Examples

## Not run: 
 # Folder
 spl_summarizeGPKGlayers(folder = "path/to/your/geopackages")

## End(Not run)

---