Association between two coordinates in R

Question

I have a problem with spatial data. I need to extract temperature data from a NetCDF file; then I need to associate this temperature at given latitude and longitude to another set of latitude and longitude contained in a different dataframe. This is the code I used to extract my variables:

myfile <- nc_open(paste(wd, 'myfile.nc', sep=''))
timearr = ncvar_get(myfile, "time")  
temp <- ncvar_get(myfile, 'temp_srf')
lat <- ncvar_get(myfile, 'lat_rho')
lon <- ncvar_get(myfile, 'lon_rho')
dim(temp)

[1] 27 75 52         # which means: 27 longitude * 75 latitudes * 52 time steps

I chose to work on the first time step of temperature for now. So:

> t1 <- as.vector(temp[,,1])

Then I created a data.frame including lat, lon and temperature in the first time step:

lat1 <- as.vector(lat)
lon1 <- as.vector(lon)
df1 <- as.data.frame(cbind(lon1, lat1, t1))
head(df1)

    lon1    lat1     t1
1 18.15338  40.48656 13.96225
2 18.24083  40.55126 14.36726
3 18.32845  40.61589 14.53822
4 18.41627  40.68045 14.78643
5 18.50427  40.74495 14.88624
6 18.59246  40.80938 14.95925

In another data frame (df2) I have some random points of latitude and longitude, that I have to associate to the closest latitude and longitude of the previous data.frame:

> df2 <- read.csv(paste(id, "myfile.csv", sep=""), header=TRUE, sep=",")
> head(df2)

    LONs     LATs
1 14.13189 43.41072
2 14.13342 43.34871
3 14.09980 43.40822
4 14.05338 43.72771
5 13.91311 43.88051
6 13.98500 43.91164

I was thinking to get the distance between each point and get the lowest one, but I don't know how to do it. Not sure if there are other solutions.

There are multiple solutions, but it depends on if you have projected or planar coordinates. Projected are like lat-long you get on your mobile phone or GPS device (which I suspect you have) and are measured in angular degrees. — Simon O'Hanlon

Simon O'Hanlon Simon O'Hanlon · Accepted Answer · 2013-03-28T15:57:57

I am assuming your data are projected coordinates, and that you need to calculate great circle distances. You can use a formula yourself (see my answer here), or you can use rdist.earth from the package fields. For each entry in df2, calculate the distance from all entries in df1, find the index of the minimum distance in that vector, and use that index to select the appropriate row df1 to assign temp to df2. It only takes one line (but it might be clearer to seperate the steps over a few commands):

require( fields )
df2["Temp"] <- df1[ sapply( seq_len( nrow(df2) ) , function(x){ which.min( rdist.earth( df2[x,] , as.matrix( df1[ c("lon1" , "lat1") ] ) , miles = FALSE, R = 6371 ) ) } ) , "t1" ]

And the results using your data:
df1
#         lon1     lat1       t1
#   1 18.15338 40.48656 13.96225
#   2 18.24083 40.55126 14.36726
#   3 18.32845 40.61589 14.53822
#   4 18.41627 40.68045 14.78643
#   5 18.50427 40.74495 14.88624
#   6 18.59246 40.80938 14.95925

df2
#         LONs     LATs     Temp
#   1 14.13189 43.41072 13.96225
#   2 14.13342 43.34871 13.96225
#   3 14.09980 43.40822 13.96225
#   4 14.05338 43.72771 14.53822
#   5 13.91311 43.88051 14.53822
#   6 13.98500 43.91164 14.78643

It looks like your distances are at least a Km apart (>300km in this data) so you should get good accuracy with the Great Circle formula. If they are smaller than 1km you may want to use the Haversine formula.

Association between two coordinates in R

2 Answers