Calculating distance between two points using the distm function inside mutate

Question

I am trying to calculate the distance between two sets of longitude and latitude coordinates.

I am using the function distm() from the package geosphere to do this.

It works fine if I manually put in the values in the distm() function, but I can't get it to work inside my mutate command.

When running it inside a mutate function I get the error:

Error in mutate_impl(.data, dots) : 
Evaluation error: Wrong length for a vector, should be 2.

@Dotpi wrote in a comment "A small note. The method geosphere:distm is not vectorized. To vectorize it use the apply functions." when he replied in this thread ( Function to calculate geospatial distance between two points (lat,long) using R )

From that I am guessing that this is what is causing the error in the mutate function, but I don't know how to solve it. I would prefer a tidyverse solution, but any help is appreciated.

Below is a test dataframe with first the code that produces the error, and then a working example where I manually insert the values from the first row in DF.

library(tidyverse)
library(geosphere)

set.seed(1)
DF <- tibble(
  Long1 = sample(1:10),
  Lat1 = sample(1:10),
  Long2 = sample(1:10),
  Lat2 = sample(1:10))

DF %>% mutate(
  Dist = distm(x= c(Long1, Lat1), y=c(Long2, Lat2), fun = distHaversine ))

distm( x = c(3, 3), y = c(10, 5), fun = distHaversine )

Answer 1

Perhaps we can use pmap

library(purrr)
pmap_dbl(DF, ~ distm(x = c(..1, ..2), y = c(..3, ..4), 
                    fun = distHaversine) %>% c)

When combined with mutate

library(dplyr)
DF %>% 
  mutate(Dist = pmap_dbl(., ~
           distm(x = c(..1, ..2), y = c(..3, ..4), fun = distHaversine)))
# A tibble: 10 x 5
#   Long1  Lat1 Long2  Lat2     Dist
#   <int> <int> <int> <int>    <dbl>
# 1     3     3    10     5  808552.
# 2     4     2     2     6  497573.
# 3     5     6     6     4  248726.
# 4     7    10     1     2 1110668.
# 5     2     5     9    10  951974.
# 6     8     7     8     8  111319.
# 7     9     8     7     9  246730.
# 8     6     4     5     1  351986.
# 9    10     1     3     7 1024599.
#10     1     9     4     3  745867.