coordinate system - Calculate distance in km to nearest points (given in lat/long) using ArcGIS DEsktop and/or R?

I have two point datasets in ArcGIS, both of which are given in WGS84 lat/lon co-ordinates and the points are spread across the whole world. I would like to find the nearest point in Dataset A to each point in Dataset B, and get the distance between them in kilometres.

This seems like a perfect use of the Near tool, but that gives me results in the co-ordinate system of the input points: that is, decimal degrees. I know I could re-project the data, but I gather (from this question) that it is difficult (if not impossible) to find a projection that will give accurate distances all over the world.

The answers to that question suggest using the Haversine formula to calculate distances using the latitude-longitude co-ordinates directly. Is there a way to do this and get a result in km using ArcGIS? If not, what is the best way to approach this?

Answer

Although this isn't an ArcGIS solution, your problem can be solved in R by exporting your points from Arc and using the spDists function from the sp package. The function finds the distances between a reference point(s) and a matrix of points, in kilometers if you set longlat=T.

Here's a quick and dirty example:

library(sp)
## Sim up two sets of 100 points, we'll call them set a and set b:
a <- SpatialPoints(coords = data.frame(x = rnorm(100, -87.5), y = rnorm(100, 30)), proj4string=CRS("+proj=longlat +datum=WGS84"))

b <- SpatialPoints(coords = data.frame(x = rnorm(100, -88.5), y = rnorm(100, 30.5)), proj4string=CRS("+proj=longlat +datum=WGS84"))

## Find the distance from each point in a to each point in b, store
##    the results in a matrix.
results <- spDists(a, b, longlat=T)