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Calculate fragment euclidean nearest neighbor distance

Source: R/lsm_distance_enn.R
lsm_distance_enn.Rd

Calculate euclidean nearest neighbor distance among fragments in meters using r.clump and r.distance GRASS GIS module.

Usage

lsm_distance_enn(
  input,
  output = NULL,
  zero_as_null = FALSE,
  id_direction = 8,
  distance_round_digit = 0,
  grid_size = 10000,
  distance_radius = 2000,
  table_distance = FALSE
)

Arguments

input

[character=""]
Habitat map, following a binary classification (e.g. values 1,0 or 1,NA for habitat,non-habitat).

output

[character=""]
Fragment fragment euclidean nearest neighbor distance map name inside GRASS Data Base.

zero_as_null

[logical=""]

table_distance

[logical=""]

id_directions

[numerical=""]

Examples

library(lsmetrics)
library(terra)

# read habitat data
r <- lsmetrics::lsm_toy_landscape(proj_type = "meters")

# plot
plot(r, legend = FALSE, axes = FALSE, main = "Binary habitat")
plot(as.polygons(r, dissolve = FALSE), lwd = .1, add = TRUE)
plot(as.polygons(r), add = TRUE)
text(r)


# find grass
path_grass <- system("grass --config path", inter = TRUE) # windows users need to find the grass gis path installation, e.g. "C:/Program Files/GRASS GIS 8.3"

# create grassdb
rgrass::initGRASS(gisBase = path_grass,
                  SG = r,
                  gisDbase = "grassdb",
                  location = "newLocation",
                  mapset = "PERMANENT",
                  override = TRUE)
#> gisdbase    grassdb 
#> location    newLocation 
#> mapset      PERMANENT 
#> rows        16 
#> columns     16 
#> north       7525600 
#> south       7524000 
#> west        234000 
#> east        235600 
#> nsres       100 
#> ewres       100 
#> projection:
#>  PROJCRS["WGS 84 / UTM zone 23S",
#>     BASEGEOGCRS["WGS 84",
#>         ENSEMBLE["World Geodetic System 1984 ensemble",
#>             MEMBER["World Geodetic System 1984 (Transit)"],
#>             MEMBER["World Geodetic System 1984 (G730)"],
#>             MEMBER["World Geodetic System 1984 (G873)"],
#>             MEMBER["World Geodetic System 1984 (G1150)"],
#>             MEMBER["World Geodetic System 1984 (G1674)"],
#>             MEMBER["World Geodetic System 1984 (G1762)"],
#>             MEMBER["World Geodetic System 1984 (G2139)"],
#>             ELLIPSOID["WGS 84",6378137,298.257223563,
#>                 LENGTHUNIT["metre",1]],
#>             ENSEMBLEACCURACY[2.0]],
#>         PRIMEM["Greenwich",0,
#>             ANGLEUNIT["degree",0.0174532925199433]],
#>         ID["EPSG",4326]],
#>     CONVERSION["UTM zone 23S",
#>         METHOD["Transverse Mercator",
#>             ID["EPSG",9807]],
#>         PARAMETER["Latitude of natural origin",0,
#>             ANGLEUNIT["degree",0.0174532925199433],
#>             ID["EPSG",8801]],
#>         PARAMETER["Longitude of natural origin",-45,
#>             ANGLEUNIT["degree",0.0174532925199433],
#>             ID["EPSG",8802]],
#>         PARAMETER["Scale factor at natural origin",0.9996,
#>             SCALEUNIT["unity",1],
#>             ID["EPSG",8805]],
#>         PARAMETER["False easting",500000,
#>             LENGTHUNIT["metre",1],
#>             ID["EPSG",8806]],
#>         PARAMETER["False northing",10000000,
#>             LENGTHUNIT["metre",1],
#>             ID["EPSG",8807]]],
#>     CS[Cartesian,2],
#>         AXIS["(E)",east,
#>             ORDER[1],
#>             LENGTHUNIT["metre",1]],
#>         AXIS["(N)",north,
#>             ORDER[2],
#>             LENGTHUNIT["metre",1]],
#>     USAGE[
#>         SCOPE["Navigation and medium accuracy spatial referencing."],
#>         AREA["Between 48°W and 42°W, southern hemisphere between 80°S and equator, onshore and offshore. Brazil."],
#>         BBOX[-80,-48,0,-42]],
#>     ID["EPSG",32723]] 

# import raster from r to grass
rgrass::write_RAST(x = r, flags = c("o", "overwrite", "quiet"), vname = "r")
#> SpatRaster read into GRASS using r.in.gdal from memory

# distance
lsmetrics::lsm_distance_enn(input = "r")
#> Converting zero as null
#> Identifying fragments
#> Calculating distance
#> [1] "1 of 1"
#>    0%   6%  12%  18%  25%  31%  37%  43%  50%  56%  62%  68%  75%  81%  87%  93% 100%
#> Changing the raster color
#> Cleaning data

# files
rgrass::execGRASS(cmd = "g.list", type = "raster")
#> r
#> r_distance_enn

# import from grass to r
r_distance_enn <- terra::rast(rgrass::read_RAST("r_distance_enn", flags = "quiet", return_format = "SGDF"))
#> Creating BIL support files...
#> Exporting raster as integer values (bytes=4)
#>    0%   6%  12%  18%  25%  31%  37%  43%  50%  56%  62%  68%  75%  81%  87%  93% 100%

# plot
plot(r_distance_enn, legend = FALSE, axes = FALSE, main = "Euclidean nearest neighbor distance (m)")
plot(as.polygons(r, dissolve = FALSE), lwd = .1, add = TRUE)
plot(as.polygons(r), add = TRUE)
text(r_distance_enn, cex = .5)


# delete grassdb
unlink("grassdb", recursive = TRUE)