How to Convert Utm Coordinates to Lat and Long in R

Convert UTM to DD while keeping label column

It goes like this:

library(sp)
d <- data.frame(x=c(0,1000), y=c(0,1000), section=1:2) 
coordinates(d) <- ~x+y
proj4string(d) = "+proj=utm +zone=1"
geo <- spTransform(d, CRS("+proj=longlat +datum=WGS84"))
as.data.frame(geo)
#  section        x           y
#1       1 178.5113 0.000000000
#2       2 178.5202 0.009019487

Or with "terra":

library(terra)
d <- data.frame(x=c(0,1000), y=c(0,1000), section=1:2) 
v <- vect(d, geom=c("x", "y"), crs="+proj=utm +zone=1")
g <- project(v, "+proj=longlat +datum=WGS84")
as.data.frame(g, geom="XY")
#  section        x           y
#1       1 178.5113 0.000000000
#2       2 178.5202 0.009019487

How to convert UTM to long/Lat while the points distributed over different zones 38,39,40,41

If all you have is the coordinate numbers and not the zone identifier then there's no way of knowing which of any of the UTM zones your points are in. The UTM coordinate numbers are repeated for each zone, and only the zone identifier can tell you which zone a point is in. The point (453199,4094292) could be anywhere in the world, never mind just those four zones in Iran.

You need to go back to your source and get the UTM zone information for each point, and then you can construct the correct projection string for each point, and do the transformation for each different UTM zone you have to get the lat-long coordinates.

Easiest way convert UTM ZONE to lat long

In order to convert UTM coordinates (easting and northing) to latitude and longitude you need the zone number and zone letter as well.
Without these your easting / northing values could be in any of the 60 zones defined by UTM.

As for libraries, there are packages for Python, Javascript and probably others.

Sample for JS:

utm.toLatLon(easting, northing, zoneNum, zoneLetter)
//returns { latitude, longitude }

utm.fromLatLon(latitude, longitude)
//returns { easting, northing, zoneNum, zoneLetter }

Converting latitude and longitude data to UTM with points from multiple UTM zones in R

UPDATE

Here is a much faster and elegant workaround using dplyr and spTransfrom

Augmented data (60k+ rows):

test_coordinates <- data.frame(x = c(13.637398, -3.58627, -5.178889), y = c(41.30736, 40.72913, 40.17528), x_correct = c(385936, 450492, 314480), y_correct = c(4573773, 4508854, 4449488 ),  zone = c(33, 30, 30), key = c(1, 2, 3), country = c("italy", "spain", "spain"))
test_coordinates = rbind(test_coordinates, test_coordinates[rep(1,60*1000),]) # simulate big data

library(dplyr)
library(sp)

get_utm <- function(x, y, zone, loc){
  points = SpatialPoints(cbind(x, y), proj4string = CRS("+proj=longlat +datum=WGS84"))
  points_utm = spTransform(points, CRS(paste0("+proj=utm +zone=",zone[1]," +ellps=WGS84")))
  if (loc == "x") {
    return(coordinates(points_utm)[,1])
  } else if (loc == "y") {
    return(coordinates(points_utm)[,2])
  }
}

test_coordinates %<>% 
  mutate(zone2 = (floor((x + 180)/6) %% 60) + 1, keep = "all"
  ) %>% 
  group_by(zone2) %>% 
  mutate(utm_x = get_utm(x, y, zone2, loc = "x"),
         utm_y = get_utm(x, y, zone2, loc = "y"))

Output (5 rows only)

test_coordinates

# A tibble: 603 × 10
# Groups:   zone2 [2]
       x     y x_correct y_correct  zone   key country zone2   utm_x    utm_y
   <dbl> <dbl>     <dbl>     <dbl> <dbl> <dbl> <chr>   <dbl>   <dbl>    <dbl>
 1 13.6   41.3    385936   4573773    33     1 italy      33 385936. 4573773.
 2 -3.59  40.7    450492   4508854    30     2 spain      30 450492. 4508854.
 3 -5.18  40.2    314480   4449488    30     3 spain      30 314480. 4449488.
 4 13.6   41.3    385936   4573773    33     1 italy      33 385936. 4573773.
 5 13.6   41.3    385936   4573773    33     1 italy      33 385936. 4573773.

ORIGINAL RESPONSE

Replace:

data.frame(t(sapply(converted_points,c)))  #Makes this list into a dataframe

With:

test_coordinates$utm_x <- unlist(converted_points)[c(T,F)]
test_coordinates$utm_y <- unlist(converted_points)[c(F,T)]

          x        y x_correct y_correct zone key country    utm_x   utm_y
1 13.637398 41.30736    385936   4573773   33   1   italy 385935.7 4573773
2 -3.586270 40.72913    450492   4508854   30   2   spain 450492.4 4508854
3 -5.178889 40.17528    314480   4449488   30   3   spain 314479.5 4449488

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