CODEWITHSUNDEEP
rutmwgs84geographic-distance
SarahBingo
SarahBingo

Reputation: 23

Converting Northing/Easting into Decimal Degrees in R

I'm trying to convert vectors that contain northing and easting data into decimal degrees using R. So far I have been able to the package rgdal to perform a projection, but I am running into a problem. The argument for the UTM zone must be a single character string, but I have multiple UTM zones in my data. Is there a way to use the rgdal::SpatialPoints() function to set multiple UTM zones? I tried inputting set character strings and using a vector in the CRS() function, but I received a warning message that only the first zone was used.


df<- data.frame(X = c(774869, 771437, 1051883, 524468), 
                Y = c(414498, 403790, 184967, 779682), 
                WGS.1984.UTM.Zone = c("57N", "57N", "54N", "59N"))

 library(rgdal)
  sputm <- SpatialPoints(df[c("X", "Y")], proj4string=CRS("+proj=utm +zone=57N +datum=WGS84"))  
  spgeo <- spTransform(sputm, CRS("+proj=longlat +datum=WGS84"))


#resultant coordinates are all transformed relative to UTM zone 57N

df$projargs<- paste("+proj=utm +zone=", df$WGS.1984.UTM.Zone, " +datum=WGS84", sep = "")

#trying again with set projargs character strings

spUTM<- SpatialPoints(df[c("X", "Y")], proj4string=CRS(df$projargs))

Warning messages:

1: In if (!is.na(projargs)) { : the condition has length > 1 and only the first element will be used

2: In if (!is.na(projargs)) { : the condition has length > 1 and only the first element will be used

3: In if (is.na(projargs)) uprojargs <- projargs else uprojargs <- paste(unique(unlist(strsplit(projargs, : the condition has length > 1 and only the first element will be used

Upvotes: 0

Views: 1312

Answers (2)

Eugene Chong
Eugene Chong

Reputation: 1741

Here's another solution with the sf package.

Make the sf object with st_as_sf(). Note the new geometry column.

library(sf)
library(dplyr)

df_sf <- st_as_sf(df,
                  coords = c("X", "Y"),
                  remove = FALSE,
                  crs = projargs)

df_sf

Simple feature collection with 4 features and 4 fields
geometry type:  POINT
dimension:      XY
bbox:           xmin: 524468 ymin: 184967 xmax: 1051883 ymax: 779682
epsg (SRID):    32657
proj4string:    +proj=utm +zone=57 +datum=WGS84 +units=m +no_defs
        X      Y WGS.1984.UTM.Zone                         projargs               geometry
1  774869 414498               57N +proj=utm +zone=57N +datum=WGS84  POINT (774869 414498)
2  771437 403790               57N +proj=utm +zone=57N +datum=WGS84  POINT (771437 403790)
3 1051883 184967               54N +proj=utm +zone=54N +datum=WGS84 POINT (1051883 184967)
4  524468 779682               59N +proj=utm +zone=59N +datum=WGS84  POINT (524468 779682)

Re-project by using st_transform() which updates the geometry column. We can pull those out into new columns with st_coordinates(), which returns a two-column matrix for every line.

df_sf_longLat <- st_transform(df_sf, crs = "+proj=longlat +datum=WGS84") %>% 
  mutate(long_degrees = st_coordinates(.)[,1],
         lat_degrees = st_coordinates(.)[,2])

df_sf_longLat

Simple feature collection with 4 features and 6 fields
geometry type:  POINT
dimension:      XY
bbox:           xmin: 159.2216 ymin: 1.667156 xmax: 163.9555 ymax: 7.053618
epsg (SRID):    4326
proj4string:    +proj=longlat +datum=WGS84 +no_defs
        X      Y WGS.1984.UTM.Zone                         projargs                  geometry long_degrees lat_degrees
1  774869 414498               57N +proj=utm +zone=57N +datum=WGS84 POINT (161.4747 3.746529)     161.4747    3.746529
2  771437 403790               57N +proj=utm +zone=57N +datum=WGS84  POINT (161.4435 3.64983)     161.4435    3.649830
3 1051883 184967               54N +proj=utm +zone=54N +datum=WGS84 POINT (163.9555 1.667156)     163.9555    1.667156
4  524468 779682               59N +proj=utm +zone=59N +datum=WGS84 POINT (159.2216 7.053618)     159.2216    7.053618

Upvotes: 1

akrun
akrun

Reputation: 887901

The function is not vectorized. So we need to loop

library(rgdal)
spUTM <- lapply(df$projargs, function(x)  
          SpatialPoints(df[c("X", "Y")], proj4string=CRS(x)))

str(spUTM)
#List of 4
# $ :Formal class 'SpatialPoints' [package "sp"] with 3 slots
#  .. ..@ coords     : num [1:4, 1:2] 774869 771437 1051883 524468 414498 ...
#  .. .. ..- attr(*, "dimnames")=List of 2
#  .. .. .. ..$ : NULL
#  .. .. .. ..$ : chr [1:2] "X" "Y"
#  .. ..@ bbox       : num [1:2, 1:2] 524468 184967 1051883 779682
#  .. .. ..- attr(*, "dimnames")=List of 2
#  .. .. .. ..$ : chr [1:2] "X" "Y"
# ...

Or use map from purrr

library(dplyr)
library(purrr)
df %>% 
     mutate(spUTM = map(projargs, ~ 
          SpatialPoints(df[c('X', 'Y')], proj4string = CRS(.x))))

Upvotes: 0

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