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GPS coordinates in the format of WGS84 are quite common. I need to transform them into Gauss-Krüger coordinates but I have no idea how to do that. The only things I know are that it is not easy and I have to use the Helmert-transformation.

I usually work with r-project and would therefore prefer to work with a r-package to solve my problem. Is there a package which could handle that?

Is it actually necessary to transform the "GPS coordinates" in order to create a hillshade map with different "landmarks" according to the coordinates? Is there any open source software to create a map and then mark the positions based on the coordinates?

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  • gis.stackexchange.com/questions/166876/… and also search the site for [r] sptransform
    – mkennedy
    Commented Nov 11, 2015 at 17:04
  • Gauss-Krüger 5 is not very specific. Do you have a well-known ID or the datum/geographic coordinate reference system and parameter values of the projection? What is your area of interest?
    – mkennedy
    Commented Nov 11, 2015 at 17:09
  • I actually just want to transform coordinates like this: 50°53'34.37"N, 13°31'21.02"E into GK coordinates RW = 3570272.656 HW = 5652121.859 and not an entire shapefile. I only need to convert 5 different GPS coordinates, which are located in Saxony/Germany and consequently have to be transformed to the GK5 - as far as I know.
    – yPennylane
    Commented Nov 13, 2015 at 9:41
  • The meridian 5 has the label 31469.
    – yPennylane
    Commented Nov 13, 2015 at 9:48

1 Answer 1

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Given that you know R you should have made a small reproducible example, but here you go.

xy <- data.frame(matrix(c(8.58, 10, 11, 10.27, 10.69, 51.52, 52.26, 51.4, 50.9, 49.43), ncol=2))

library(sp)
colnames(xy) <- c('lon', 'lat')
coordinates(xy) <- ~ lon + lat
proj4string(xy) <- CRS("+proj=longlat +datum=WGS84")

p <- spTransform(xy, CRS("+proj=tmerc +lat_0=0 +lon_0=27 +k=1 +x_0=5500000 +y_0=0 +ellps=krass +units=m +no_defs"))
# see http://spatialreference.org/ref/epsg/pulkovo-1942-gauss-kruger-zone-5/

gauss <- coordinates(p)
colnames(gauss) <- c('x', 'y')
gauss
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