Calculates distance statistics from cells or samples to their assigned stratum centroids. Provides mean, standard deviation, minimum, maximum, and median distances for each stratum.
Value
A data frame with one row per stratum containing:
- stratum_id
Stratum identifier
- n_cells or n_samples
Number of cells (for ss_strata) or samples (for ss_samples)
- mean_dist
Mean distance to centroid
- sd_dist
Standard deviation of distances
- min_dist
Minimum distance to centroid
- max_dist
Maximum distance to centroid
- median_dist
Median distance to centroid
Details
For ss_strata objects, the function computes distances from all grid cells to their assigned stratum centroids. For ss_samples objects, it computes distances from sample points to centroids.
The function automatically detects coordinate system type (planar vs lat/lon) and uses appropriate distance calculations:
Planar coordinates: Euclidean distance
Geographic coordinates (lat/lon): Haversine distance (great circle)
By default, squared distances are returned for computational efficiency and
consistency with the MSSD (Mean Squared Shortest Distance) metric used in
stratification. Set actual_distance = TRUE to get actual distances.
Examples
if (FALSE) { # \dontrun{
library(sf)
# Create study area and stratification
poly <- st_polygon(list(rbind(
c(0, 0), c(100, 0), c(100, 50), c(0, 50), c(0, 0)
)))
study_area <- st_sf(geometry = st_sfc(poly))
set.seed(42)
strata <- ss_stratify(study_area, n_strata = 20, n_try = 5)
# Distance summary for strata
dist_summary <- ss_distance_summary(strata)
print(dist_summary)
# Distance summary for samples
samples <- ss_coverage(strata)
dist_samples <- ss_distance_summary(samples, actual_distance = TRUE)
print(dist_samples)
} # }