This function allows you to calculate the standard deviation of shape index of all patches belonging to one class in a categorical landscape in vector data format shape index is the ratio between the actual perimeter of the patch and the hypothetical minimum perimeter of the patch. The minimum perimeter equals the perimeter if the patch would be maximally compact. That means, the perimeter of a circle with the same area of the patch.

vm_c_shape_sd(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 standard deviation of each class is 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.

Examples

vm_c_shape_sd(vector_landscape, "class")
#> # A tibble: 3 × 5
#>   level class id    metric   value
#>   <chr> <chr> <chr> <chr>    <dbl>
#> 1 class 1     NA    shape_sd    NA
#> 2 class 2     NA    shape_sd    NA
#> 3 class 3     NA    shape_sd    NA