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Remove unique outliers from raster files

Source: R/remove_unique_outliers.R
remove_unique_outliers.Rd

remove_unique_outliers() removes unique outliers from raster files (GeoTIFF or Esri ASCII raster format) based on the interquartile range (IQR).

This function processes each raster file by reading its values, identifying unique outliers using the unique_outliers() function, and replacing those outlier values with NA. The modified raster is then saved back to the same file, effectively overwriting the original data.

Note: This function requires the fs package to be installed.

Usage

remove_unique_outliers(file, n_iqr = 1.5)

Arguments

file

A character vector with the file paths of the raster files to be processed. Supported file formats are GeoTIFF (.tif or .tiff) and Esri ASCII raster (.asc).

n_iqr

(optional) A number specifying the multiplier of the interquartile range (IQR) to define outliers. See unique_outliers() to learn more (default: 1.5).

Value

An invisible NULL value. This function is used for its side effects.

See also

Other utility functions: closest_geobr_year(), fix_postal_code(), map_fill_data(), test_geobr_connection(), unique_outliers()

Examples

# Set the Environment -----

library(readr)
#> 
#> Attaching package: ‘readr’
#> The following object is masked from ‘package:curl’:
#> 
#>     parse_date
library(terra)

# Create a Fictional Esri ASCII File -----

asc_content <- c(
  "ncols         5",
  "nrows         5",
  "xllcorner     0.0",
  "yllcorner     0.0",
  "cellsize      1.0",
  "NODATA_value  -9999",
  "1 2 3 4 5 ",
  "6 7 8 9 10 ",
  "11 12 1000 14 15 ", # Extreme outlier (1000)
  "16 1 18 19 20 ",
  "21 22 23 24 25 "
)

temp_file <- tempfile(fileext = ".asc")

asc_content |> write_lines(temp_file)

# Visualize Values Before `remove_unique_outliers()` -----

temp_file |> rast() |> values(mat = FALSE)
#>  [1]    1    2    3    4    5    6    7    8    9   10   11   12 1000   14
#> [15]   15   16    1   18   19   20   21   22   23   24   25

# Visualize Values After `remove_unique_outliers()` -----

temp_file |> remove_unique_outliers()

temp_file |> rast() |> values(mat = FALSE)
#>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 NA 14 15 16  1 18 19 20 21 22 23 24
#> [25] 25