Landscape shape index (vector data) — vm_c

This function allows you to calculate the ratio between the actual edge length of class i and the hypothetical minimum edge length of class i in a categorical landscape in vector data format. The minimum edge length equals the edge length if class i would be maximally aggregated into a circle.

Usage

vm_c_lsi(landscape, class_col)

Arguments

landscape: the input landscape image,
class_col: the name of the class column of the input landscape

Value

the returned calculated index are in column "value", and this function returns also some important information such as level, class number and metric name. Moreover, the "id" column, although it is just NA here at class level. we need it because the output struture of metrics at class level should correspond to patch level one by one, and then it is more convinient to combine metric values at different levels and compare them.

Details

LSI is calculated as: LSI = TE / (2 * pi * sqrt(CA/pi)) where TE is the total edge (in meters) and CA is the class area (in square meters). This uses circle standardization, which is more natural for vector data. An LSI of 1 indicates a perfectly circular class. Note: This differs from landscapemetrics which uses square standardization.

Examples

vm_c_lsi(vector_landscape, "class")
#> # A tibble: 3 × 5
#>   level class id    metric value
#>   <chr> <chr> <chr> <chr>  <dbl>
#> 1 class 1     NA    lsi     5.06
#> 2 class 2     NA    lsi     4.76
#> 3 class 3     NA    lsi     4.80