如果tidyverse方法可以，我们可以在mutate()中使用purrr::map()为每个多边形生成一个包含5个样本点的列表。当得到的列表列是非嵌套的，我们将有一个sf对象的多边形和点，行为每个采样点和所有属性的原始多边形sf。我们现在可以将几何体切换为点列，并删除不需要的列。

library(sf)
library(dplyr)
library(ggplot2)
library(tidyr)

# generate sample data, 5 overlapping circles + id attribute
set.seed(42)
c_df <- list(matrix(c(0,0,10,0,10,10,0,10,0,0),ncol=2, byrow=TRUE)) %>% 
  st_polygon() %>% 
  st_sample(size = 5) %>% 
  st_buffer(4) %>% 
  st_as_sf() %>% 
  st_set_geometry("geometry") %>% 
  mutate(id = row_number()) %>% 
  as_tibble() %>% st_as_sf()

c_df
#> Simple feature collection with 5 features and 1 field
#> Geometry type: POLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -1.138605 ymin: -2.653334 xmax: 13.37075 ymax: 11.36588
#> CRS:           NA
#> # A tibble: 5 × 2
#>                                                                   geometry    id
#>                                                                  <POLYGON> <int>
#> 1 ((13.14806 5.190959, 13.14258 4.981616, 13.12615 4.772846, 13.09881 4.5…     1
#> 2 ((13.37075 7.365883, 13.36527 7.156539, 13.34884 6.947769, 13.32151 6.7…     2
#> 3 ((6.861395 1.346666, 6.855913 1.137322, 6.839483 0.9285521, 6.812149 0.…     3
#> 4 ((12.30448 6.569923, 12.29899 6.360579, 12.28256 6.151809, 12.25523 5.9…     4
#> 5 ((10.41746 7.050648, 10.41197 6.841304, 10.39554 6.632534, 10.36821 6.4…     5

# sample 5 points from each polygon , 5 × 3 tibble, points are stored in a list-column 
# unnest sample_points list-column, resulting tibble is 25 × 3
# switch geometry column; resulting sf object includes poly_id with polygon id's
sampled_points <- c_df %>% 
  mutate(sample_points = purrr::map(geometry, st_sample, 5)) %>% 
  unnest_longer(sample_points) %>% 
  st_set_geometry("sample_points") %>% 
  select(poly_id = id)

结果：

sampled_points
#> Simple feature collection with 25 features and 1 field
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: 3.755624 ymin: 0.01408366 xmax: 13.28189 ymax: 9.854324
#> CRS:           NA
#> # A tibble: 25 × 2
#>    poly_id       sample_points
#>      <int>             <POINT>
#>  1       1 (8.809995 9.016771)
#>  2       1 (10.90096 2.130858)
#>  3       1 (12.62544 4.990936)
#>  4       1 (7.191491 5.673621)
#>  5       1 (8.846403 8.423211)
#>  6       2  (13.28189 6.94164)
#>  7       2 (6.030255 9.266648)
#>  8       2 (9.484448 9.854324)
#>  9       2 (8.492382 6.470749)
#> 10       2 (12.61666 8.847241)
#> # ℹ 15 more rows

mutate(sampled_points, poly_id = as.factor(poly_id)) %>% 
  ggplot() +
  geom_sf(data = mutate(c_df, id = as.factor(id)), aes(fill = id), alpha = .5) +
  geom_sf_text(aes(label = poly_id), nudge_x = -.25, nudge_y = -.25) +
  geom_sf(aes(fill = poly_id), shape = 21, size = 3) +
  scale_fill_viridis_d() +
  scale_color_viridis_d() +
  theme_void()

创建于2023-06-04使用reprex v2.0.2