Calculate statistics for vectors

Usage

lsm_vector_statistic(
  input,
  output = NULL,
  landscape_metric,
  landscape_metric_has_null = FALSE,
  vector,
  type,
  column_prefix,
  method = "average",
  percentile = NULL
)

Arguments

input: [character=""]
output: [character=""]
Map name output inside GRASS Data Base.
landscape_metric: [character=""]
landscape_metric_has_null: [character=""]
vector: [character=""]
type: [character=""]
column_prefix: [character=""]
method: [character=""]
Univariate statistics: number, null_cells, minimum ,maximum, range, average, stddev, variance, coeff_var, sum, first_quartile ,median, third_quartile, percentile
percentile: [character=""]

Examples

library(lsmetrics)
library(terra)

# read habitat data
r <- lsmetrics::lsm_toy_landscape()

# 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["unknown",
#>     BASEGEOGCRS["unknown",
#>         DATUM["World Geodetic System 1984",
#>             ELLIPSOID["WGS 84",6378137,298.257223563,
#>                 LENGTHUNIT["metre",1]],
#>             ID["EPSG",6326]],
#>         PRIMEM["Greenwich",0,
#>             ANGLEUNIT["degree",0.0174532925199433],
#>             ID["EPSG",8901]]],
#>     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]],
#>         ID["EPSG",17023]],
#>     CS[Cartesian,2],
#>         AXIS["(E)",east,
#>             ORDER[1],
#>             LENGTHUNIT["metre",1,
#>                 ID["EPSG",9001]]],
#>         AXIS["(N)",north,
#>             ORDER[2],
#>             LENGTHUNIT["metre",1,
#>                 ID["EPSG",9001]]]] 

# import raster from r to grass
rgrass::write_RAST(x = r, flags = c("o", "overwrite", "quiet"), vname = "r", verbose = FALSE)

# vector
p <- terra::vect(data.frame(x = c(235150, 234450, 235150),
                            y = c(7525250, 7524850, 7524350)),
                 geom = c("x", "y"),
                 crs = "+proj=utm +zone=23 +south +datum=WGS84 +units=m +no_defs +type=crs")

# import raster from r to grass
rgrass::write_VECT(x = p, flags = c("o", "overwrite", "quiet"), vname = "p")

# area
lsmetrics::lsm_fragment_area(input = "r", id = TRUE, ncell = TRUE, area_integer = TRUE)
#> Converting zero as null
#> Identifying the fragmentes
#> Counting the cell number of fragmentes
#> First pass
#>    0%   6%  12%  18%  25%  31%  37%  43%  50%  56%  62%  68%  75%  81%  87%  93% 100%
#> Writing output map
#>    0%   6%  12%  18%  25%  31%  37%  43%  50%  56%  62%  68%  75%  81%  87%  93% 100%
#> Calculating the area of fragmentes

# vector statistics
lsmetrics::lsm_vector_statistic(input = "r",
                                landscape_metric = "r_fragment_area_ha",
                                landscape_metric_has_null = TRUE,
                                vector = "p",
                                type = "point",
                                column_prefix = "area",
                                method = "average")
#> Processing input data (3 categories)...
#> Adding columns '['area_average DOUBLE PRECISION']'
#> Adding column <area_average> to the table
#>    6%  12%  18%  25%  31%  37%  43%  50%  56%  62%  68%  75%  81%  87%  93% 100%
#>  100%
#> Updating the database ...
#> Statistics calculated from raster map <r_fragment_area_ha_binary> and
#> uploaded to attribute table of vector map <p>.

# files
# rgrass::execGRASS(cmd = "g.list", type = "vector")

# import from grass to r
r_fragment_area <- rgrass::read_RAST("r_fragment_area_ha", flags = "quiet", return_format = "terra")

# import point
v_point <- rgrass::read_VECT("p", flags = "quiet")

# plot
plot(r_fragment_area, legend = FALSE, axes = FALSE, main = "Fragment area (ha)")
plot(as.polygons(r, dissolve = FALSE), lwd = .1, add = TRUE)
plot(as.polygons(r), add = TRUE)
text(r_fragment_area)
plot(v_point, "area_average", legend = FALSE, cex = 3, add = TRUE)
plot(p, col = "gray30", cex = 3, add = TRUE)
text(v_point, col = "white", labels = "area_average", cex = .7)


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