Geospatial Distance Between Two Points in R (Example)


In this article, I’ll illustrate how to calculate different types of geographical distance metrics in the R programming language.

The page looks as follows:

Here’s the step-by-step process.


Constructing Example Data

The first step is to create some example data:

my_points <- matrix(c(77.65465, 91.54323,    # Create longitude/latitude matrix
                      21.35444, 17.65465),
                    nrow = 2)
colnames(my_points) <- c("longitude", "latitude")
rownames(my_points) <- c("pt_1", "pt_2")
my_points                                    # Print longitude/latitude matrix


table 1 matrix geospatial distance between two points r


Table 1 shows the structure of our example data: It is composed of two geographical latitude and longitude points.

In this tutorial, I’ll show different ways on how to measure the geospatial distance between these two points in R.

Let’s do this!


Example 1: Calculate Geospatial Distance Using geosphere Package

This example explains how to compute different measures of distance in the R programming language.

All distance metrics that I’ll explain in this tutorial are provided by the geosphere add-on package.

We first have to install and load the geosphere package to RStudio, if we want to use the corresponding functions:

install.packages("geosphere")                # Install geosphere package
library("geosphere")                         # Load geosphere package

Now, we can use the different distance functions provided by the geosphere package. Besides others, we can calculate the Haversine distance

distHaversine(my_points)                     # Calculate Haversine distance
# [1] 1513707

…the Law of Cosines distance

distCosine(my_points)                        # Calculate Law of Cosines distance
# [1] 1513707

…the Meeus distance

distMeeus(my_points)                         # Calculate Meeus distance
# [1] 1513607

…the distance along a rhumb line

distRhumb(my_points)                         # Calculate rhumb distance
# [1] 1514123

…the Vincenty ellipsoid distance

distVincentyEllipsoid(my_points)             # Calculate Vincenty ellipsoid distance
# [1] 1513608

…and the Vincenty sphere distance:

distVincentySphere(my_points)                # Calculate Vincenty sphere distance
# [1] 1513707

Not all the previously used distance metrics return the same result. However, the differences between the metrics are not very large.


Example 2: Calculate Geospatial Distance Matrix Using distm() Function

The geosphere package also provides the possibility to create a distance matrix. This is especially useful when you are dealing with many longitude and latitude points.

For this, we can use the distm function of the geosphere package.

In this example, I’ll explain how to calculate the distance on an ellipsoid by specifying the fun argument to be equal to distGeo. However, we may use any other function that I have explained in this tutorial as distance metric.

Let’s apply the distm function in R:

dist_mat <- distm(my_points, fun = distGeo)  # Apply distm function
dist_mat                                     # Print distance matrix


table 2 matrix geospatial distance between two points r


After running the previous syntax the distance matrix shown in Table 2 has been created.


Video & Further Resources

Would you like to know more about geospatial distances? Then I can recommend watching the following video of my YouTube channel. In the video, I’m explaining the content of this article:


The YouTube video will be added soon.


Furthermore, you may have a look at the other articles about measuring geographical distances in R that I have published on my homepage:


Summary: This tutorial has illustrated how to compute geographical distance metrics in R programming. In case you have any additional questions, don’t hesitate to let me know in the comments section.


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8 Comments. Leave new

    February 11, 2021 10:57 pm

    small error in syntax
    distm(my_points, fun = distGeo) # Apply distm function
    dist_mat # Print distance matrix

    should be
    dist_mat<-distm(my_points, fun = distGeo) # Apply distm function
    dist_mat # Print distance matrix

    February 11, 2021 11:01 pm

    is there any way to see the coding for the function distHaversine? My information about the Haversine formula is that it is pretty simple. However, I get a discrepancy between the result printed here and what I calculate with the Haversine formula. My result is 1544021 not 1513707 (I assume the output is meters).

    • Hi again 🙂

      Generally speaking: In RStudio, you can get the source code of every function by marking the function and pressing the F2 key (more information).

      The distHaversine has the following source code:

      function (p1, p2, r = 6378137) 
        toRad <- pi/180
        p1 <- .pointsToMatrix(p1) * toRad
        if (missing(p2)) {
          p2 <- p1[-1, , drop = FALSE]
          p1 <- p1[-nrow(p1), , drop = FALSE]
        else {
          p2 <- .pointsToMatrix(p2) * toRad
        p = cbind(p1[, 1], p1[, 2], p2[, 1], p2[, 2], as.vector(r))
        dLat <- p[, 4] - p[, 2]
        dLon <- p[, 3] - p[, 1]
        a <- sin(dLat/2) * sin(dLat/2) + cos(p[, 2]) * cos(p[, 4]) * 
          sin(dLon/2) * sin(dLon/2)
        a <- pmin(a, 1)
        dist <- 2 * atan2(sqrt(a), sqrt(1 - a)) * p[, 5]



  • Hello Joachim

    Thanks for your post. I have a dataset with 60 000 points that depict a river course (pixel extracts from satellite image). The pixels are ordered ascendingly from source to outlet with an ID and each pixel has latitude and longitude. I need to know the distance in meters between two consecutive points. I fail to use distm() since it would result in a hugh matrix that exceeds the computer’s memory. How can I deal with this ? Many thanks.

  • Hi, I’m applying ” dist_mat<-distm(my_points, fun = distGeo) # Apply distm function
    dist_mat # Print distance matrix " on my data points matrix and getting an error: Error in .pointsToMatrix(x) : longitude < -360

    Could you please help?


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