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Landscape fragmentation metrics

geo_landscape.Rd

geo_landscape() measures how fragmented each class of a categorical raster (land cover, habitat, forest/non-forest) is, with the standard FRAGSTATS metrics (McGarigal and Marks 1995) as in the GeoSpaX fragmentation plug-in. Patches are built with 8-neighbour rules; areas are in hectares and edges in metres, measured on the ground for both projected and geographic rasters.

Class-level metrics: np (number of patches), ca (class area, ha), pland (share of the landscape, %), lpi (largest patch index, %), area_mn (mean patch area, ha), ed (edge density, m/ha), ai (aggregation index, %; He et al. 2000) and mesh (effective mesh size, ha; Jaeger 2000), the expected size of the patch a randomly placed animal finds itself in. Landscape-level metrics add Shannon's (shdi) and Simpson's (sidi) diversity of classes.

Usage

geo_landscape(x, level = c("class", "landscape"))

Arguments

x

A categorical SpatRaster (integer classes; NA is outside the landscape).

level

"class" or "landscape".

Value

A tibble: one row per class (level = "class") or one row.

References

He HS, DeZonia BE, Mladenoff DJ (2000) An aggregation index (AI) to quantify spatial patterns of landscapes. Landscape Ecology 15:591-601.

Jaeger JAG (2000) Landscape division, splitting index, and effective mesh size. Landscape Ecology 15:115-130.

McGarigal K, Marks BJ (1995) FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. USDA Forest Service General Technical Report PNW-351.

See also

geo_dbscan().

Examples

r <- terra::rast(nrows = 30, ncols = 30, xmin = 0, xmax = 3000,
  ymin = 0, ymax = 3000, crs = "EPSG:32631")
terra::values(r) <- rep(c(1, 2), length.out = 900)
geo_landscape(r)
#> # A tibble: 2 × 9
#>   class    np    ca pland   lpi area_mn    ed    ai  mesh
#>   <dbl> <int> <dbl> <dbl> <dbl>   <dbl> <dbl> <dbl> <dbl>
#> 1     1    15   450    50  3.33      30  96.7  50.8    15
#> 2     2    15   450    50  3.33      30  96.7  50.8    15