I have a DEM file in QGIS and would like to import the the satellite image for the same region into R.

According to QGIS, the CRS used in the DEM file is:

Layer Spatial Reference System
+proj=somerc +lat_0=46.95240555555556 +lon_0=7.439583333333333 +k_0=1 +x_0=2600000 +y_0=1200000 +ellps=bessel +towgs84=674.374,15.056,405.346,0,0,0,0 +units=m +no_defs

Layer Extent (layer original source projection)
696584.9723235532874241,167580.0099993922340218 : 696800.0223235532175750,167790.0099993922049180

To download a satelite image I am using get_map. However this only works with long/lat format and I need to convert my projected coordinates into long/lat.

Is there a way how to easily convert the layer extent to long/lat?

I have tried to do the conversion myself using spTransform. Firstly, I have converted the layer extent from QGIS (upper left corner coordinates and lower right corner coordinates) into bbox format (easting, northings).

  # first row: eastings (x-axis, longitude)
  # second row: northings (y-axis, latitude)
eastings <- c(696584.9723235532874241, 696800.0223235532175750)
northings <- c (167580.0099993922340218, 167790.0099993922049180)
coords_bbox <- cbind(eastings, northings)

> coords_bbox_pts
class       : SpatialPoints 
features    : 2 
extent      : 696585, 696800, 167580, 167790  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=somerc +lat_0=46.95240555555556 +lon_0=7.439583333333333 +k_0=1 +x_0=2600000 +y_0=1200000 +ellps=bessel +towgs84=674.374,15.056,405.346,0,0,0,0 +units=m +no_defs 

According to my knowledge, the spTransform function works only on Spatial* and therefore I have converted bbox to SpatialPoints and then used the SPatialPoints as input for the spTransform function.

coords_bbox_pts <- SpatialPoints(coords = coords_bbox, proj4string=CRS("+proj=somerc +lat_0=46.95240555555556 +lon_0=7.439583333333333 +k_0=1 +x_0=2600000 +y_0=1200000 +ellps=bessel +towgs84=674.374,15.056,405.346,0,0,0,0 +units=m +no_defs"))

longlatcoor <- spTransform(coords_bbox_pts,CRS("+proj=longlat +lat_0=46.95240555555556 +lon_0=7.439583333333333 +k_0=1 +x_0=2600000 +y_0=1200000 +ellps=bessel +towgs84=674.374,15.056,405.346,0,0,0,0 +units=m +no_defs"))

> longlatcoor
class       : SpatialPoints 
features    : 2 
extent      : -13.40025, -13.3986, 35.41811, 35.42041  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=longlat +lat_0=46.95240555555556 +lon_0=7.439583333333333 +k_0=1 +x_0=2600000 +y_0=1200000 +ellps=bessel +towgs84=674.374,15.056,405.346,0,0,0,0 +units=m +no_defs 

I was expecting to obtain a satellite image of a part of the Swiss Alps, but I have clearly done something wrong, because the output I have obtained is not what I expected.


# Set a range
lat <- c(-13.40025, -13.3986)                
lon <- c(35.41811, 35.42041)   

# Get a map
map <- get_map(location = c(lon = mean(lon), lat = mean(lat)), zoom = 14,
               maptype = "satellite", source = "google")

What is the problem?

I am not a geographer, there may be quite likely some trivial issue with my thinking.

  • The CRS definition is CH1903+ / LV95 (EPSG:2056), but your data's extent matches CH1903 / LV03 (EPSG:21781). The main differences are the x_0 and y_0 values which are 600000 and 200000, respectively.
    – mkennedy
    Commented Mar 26, 2018 at 0:10
  • @mkennedy could you elaborate your comment? i do not understand. How do I know that my CRS definition matches the CH1903+ / LV95 (EPSG:2056) projection? How is it possible that my CRS and data extent match different projections? What do the values x_0 and y_0 stand for?
    – user1607
    Commented Mar 26, 2018 at 8:35
  • x_0 and y_0 are the "false easting" and "false northing" parameters. They reset the coordinates at the origin/center point of the CRS. You can look up CRS at epsg-registry.org or look at proj4 strings at spatialreference.org.
    – mkennedy
    Commented Mar 26, 2018 at 19:02
  • Generally, data coordinates will be similar to the false easting/northing values. The data is reporting +x_0=2600000 +y_0=1200000 in the CRS definition, but the bbox values are 696k,168k so 2million and 1million different. For EPSG:21781, they're +x_0=600000 +y_0=200000 so you see they match much better.
    – mkennedy
    Commented Mar 26, 2018 at 19:05

1 Answer 1


maybe something like this. Always check the order of the xmin,xmax,ymin,ymax arguments. These routinly change across different packages & objects

filepathtodem <- "C:/Users/...../mydem.tif" # Change for your computer

# Load libraries

# Load your DEM
r <- raster(filepathtodem)
# Check projection of your raster
# Get the extent of your raster dem
r_ext <- extent(r)
# Convert the extent to a spatial polygon
ext_poly <- as(r_ext, 'SpatialPolygons')  
# Assign projection to this new spatial polygon (no tranformation yet)
projection(ext_poly) <- projection(r)

# Transform spatial polygon to new projection of your choice
# http://spatialreference.org/ref/epsg/wgs-84/
# For this example, lets use 4326 (Google Earth/Bing ect)
new_poly <- spTransform(ext_poly, CRS("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"))
projection(ext_poly) # Does the new projection look ok 
extent(ext_poly) # New extent of transformed polygon
  • How do I choose the projection? For the second projection command, did you mean projection(new_poly) ? Your approach give me almost the same results as mine: class : Extent xmin : -13.40088 xmax : -13.39798 ymin : 35.4181 ymax : 35.42043 vs. class : Extent xmin : -13.39837 xmax : -13.39672 ymin : 35.41824 ymax : 35.42055 and the displayed map is now even close to the imported .tif file.
    – user1607
    Commented Mar 26, 2018 at 8:44

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