Spatial nearest neighbor assignment in R

Question

I am working on a study that is trying to assign particulate matter exposure to specific individuals based on their addresses. I have two data sets with longitude and lati

Answer 1

If you have a big dataset you might want to use the very efficient nabor package as explained by @user3507085 in this answer. Since the question is closed as off-topic I have copy-pasted the answer below, so it "stays alive" in this thread. I don't know if this is considered bad practice and I'm happy to delete/edit if requested (note the distances given by knn are not the geographical distances, but I guess they could be converted to spherical distances by a simple transformation including arcsin):

lonlat2xyz=function (lon, lat, r) 
{
lon = lon * pi/180
lat = lat * pi/180
if (missing(r)) 
    r <- 6378.1
x <- r * cos(lat) * cos(lon)
y <- r * cos(lat) * sin(lon)
z <- r * sin(lat)
return(cbind(x, y, z))
}

lon1=runif(100,-180,180);lon2=runif(100,-180,180);lat1=runif(100,-90,90);lat2=runif(100,-90,90)

xyz1=lonlat2xyz(lon1,lat1)
xyz2=lonlat2xyz(lon2,lat2)

library(nabor)

out=knn(data=xyz1,query = xyz2,k=20)

library(maps)

map()
points(lon1,lat1,pch=16,col="black")
points(lon2[1],lat2[1],pch=16,col="red")
points(lon1[out$nn.idx[1,]],lat1[out$nn.idx[1,]],pch=16,col="blue")