How to do spatial join of polygons to nearest point using polygon boundry?

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I have polygons (polygon.shp). I want to match the nearest points to the polygons. The link to the file LINK

I am trying to achieve the following task:

  1. Calculate the distance to the nearest point from the boundary of the polygon (NOT from the centroid of polygons)
  2. For some polygons I have to match more than one nearest point (see "no_matches" attribute)

In the final output I am planning to achieve the following information: Column: id, no_matches, point_id_1, distance_1, point_id_2, distance_2, point_id_3, distance_3

setwd("~/example")
library(sf)
polygon <- st_read("polygon.shp")
point <- st_read("point.shp")

nearest = try(sf::st_nearest_feature(polygon, point))
ls = sf::st_nearest_points( polygon, point[nearest], pairwise = F)

I get the following error:

Error in `[.data.frame`(x, i) : undefined columns selected

Any idea how could I achieve this task?

sp sf gis geospatial r
1 Answers

Consider this piece of code; what it does is:

  • iterates over your polygons object, creating 1 row in results dataframe for each iteration
  • for a given polygon finds indices of nearest points; this will be, depending on the value of no_matches column, vector of length one to three
  • for each iteration find distance from your polygon to three points in the nearest vector; should the nearest vector have length less than 3 (as specified by no_matches column) NA will be returned.

Given the need to find more than 1 nearest object (which I kind of missed in my previous answer, now deleted) you will be better off with nngeo::st_nn() than sf::st_nearest_feature(). Using sf::st_distance() for calculating distance remains.

It is necessary to iterate (via a for cycle or some kind of apply) because the k argument of nngeo::st_nn() is not vectorized.

library(sf)
library(dplyr)

points <- st_read("./example/point.shp")
polygons <- st_read("./example/polygon.shp")

result <- data.frame() # initiate empty result set

for (i  in polygons$id) { # iterate over polygons
  
  # ids of nearest points as vector of lenght one to three
  nearest <- nngeo::st_nn(polygons[polygons$id == i, ], 
                          points, 
                          k = polygons[polygons$id == i, ]$no_matches,
                          progress = F)[[1]]
  
  # calculate result for current polygon
  current <- data.frame(id = i,
                        # id + distance to first nearest point
                        point_id_1 = points[nearest[1], ]$point_id,
                        distance_1 = st_distance(polygons[polygons$id == i, ],
                                                 points[nearest[1], ]),
                        # id + distance to second nearest point (or NA)
                        point_id_2 = points[nearest[2], ]$point_id,
                        distance_2 = st_distance(polygons[polygons$id == i, ],
                                                 points[nearest[2], ]),
                        # id + distance to third nearest point (or NA)
                        point_id_3 = points[nearest[3], ]$point_id,
                        distance_3 = st_distance(polygons[polygons$id == i, ],
                                                 points[nearest[3], ])
  )
  
  
  # add current result to "global" results data frame
  result <- result %>% 
    bind_rows(current)
  
}

# check results
result
user_77568890
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