Calculating distance over a list

Question

I have two list of coordinates, mapped_coords, unmapped_coords that are both a list of coordinates.

I want to take the unmapped_coords and for every element return the index of the point with the min distance in mapped_coord.

> head(mapped_coords)
[[1]]
[1] -79.2939  43.8234

[[2]]
[1] -79.7598  43.4381

[[3]]
[1] -79.4569  43.6693

[[4]]
[1] -81.2472  42.9688

[[5]]
[1] -79.1649  43.8073

[[6]]
[1] -79.7388  43.6753

 str(mapped_coords)
List of 62815
 $ : num [1:2] -79.3 43.8
 $ : num [1:2] -79.8 43.4
 $ : num [1:2] -79.5 43.7

Using the geosphere package I can use distHaversine to calculate the distance of aa pair but I'm not sure of how to do it over the entire list.

> distHaversine(unlist(unmapped_coords[1]), unlist(mapped_coords[1]))
[1] 100594.6

Answer 1

You can use geosphere::distm to make a distance matrix, of which you can find the minimum column (besides the diagonal, which is not useful) with which.min :

l <- list(c(-79.2939, 43.8234), 
          c(-79.7598, 43.4381), 
          c(-79.4569, 43.6693), 
          c(-81.2472, 42.9688), 
          c(-79.1649, 43.8073), 
          c(-79.7388, 43.6753))

m <- geosphere::distm(do.call(rbind, l))
diag(m) <- NA

apply(m, 1, which.min)
#> [1] 5 6 1 2 1 3

If you have a second list of distances, pass that as the second parameter to distm , making the diagonal useful. Since there will be no NA s, the minimum column can be calculated with max.col(-m) .

Answer 2

You can give as input to distHaversine a pair of coordinates and a matrix of coordinates (with 2 columns), and that will return a vector of distances of the same length as the number of rows in the matrix. You can loop through your list of unmapped coordinates using lapply :

Data:

mapped_coord = list(c(-79.29,43.82),c(-79.76,43.44))
[[1]]
[1] -79.29  43.82

[[2]]
[1] -79.76  43.44

unmapped_coord = list(c(-79.16,43.12),c(-80.52,42.95))
[[1]]
[1] -79.16  43.12

[[2]]
[1] -80.52  42.95

Method:

library(geosphere)
## Transform the list of mapped coordinates into a matrix
mat = do.call(rbind,mapped_coord)
      [,1]  [,2]
[1,] -79.29 43.82
[2,] -79.76 43.44
## Find the coordinates with the min distances
lapply(unmapped_coord,function(x) which.min(distHaversine(x,mat)))
[[1]]
[1] 2

[[2]]
[1] 2