Convert ‘MGRS’ (‘Military Grid Reference System’) Coordinates From/To Other Coordinate Systems
Description
The ‘Military Grid Reference System’ (‘MGRS’) is the geocoordinate standard used by ‘NATO’ militaries for locating points on the earth. The ‘MGRS’ is derived from the ‘Universal Transverse Mercator’ (‘UTM’) grid system and the universal polar stereographic (‘UPS’) grid system, but uses a different labeling convention. The ‘MGRS’ is used for the entire earth. Methods are provided to convert ‘MGRS’ coordinates to and from other coordinate systems.
Essentially, a lightweight R wrapper around bits of https://svn.osgeo.org/gdal/trunk/gdal/frmts/nitf/.
Decent reference on MGRS & UTM (Universal Transverse Mercator): https://www.luomus.fi/en/utm-mgrs-atlas-florae-europaeae.
The origin of the MGRS grid, in the Pacific. Honolulu is in 4QFJ.
The origin of the MGRS grid, in the Pacific. Honolulu is in 4QFJ.
What’s Inside The Tin
The following functions are implemented:
-
latlng_to_mgrs: Convert latitude/longitude to MGRS string -
mgrs_precision: Return MGRS grid reference precision (in meters) -
mgrs_to_latlng: Convert an MGRS string to latitude/longitude -
mgrs_to_ups: Convert MGRS to UPS -
mgrs_to_utm: Convert MGRS to UTM -
ups_to_latlng: Convert UPS to Latitude/Longitude -
ups_to_mgrs: Convert UPS to MGRS -
utm_to_latlng: Convert UTM to Latitude/Longitude -
utm_to_mgrs: Convert UTM to MGRS
Installation
install.packages("mgrs", repos = "https://cinc.rud.is")
# or
remotes::install_git("https://git.rud.is/hrbrmstr/mgrs.git")
# or
remotes::install_git("https://git.sr.ht/~hrbrmstr/mgrs")
# or
remotes::install_gitlab("hrbrmstr/mgrs")
# or
remotes::install_bitbucket("hrbrmstr/mgrs")
# or
remotes::install_github("hrbrmstr/mgrs")NOTE: To use the ‘remotes’ install options you will need to have the {remotes} package installed.
Usage
library(mgrs)
library(hrbrthemes)
library(tidyverse)
# current version
packageVersion("wand")
## [1] '0.6.0'Basics
mgrs_to_latlng("33UXP04")
## mgrs lat lng
## 1 33UXP04 48.20535 16.34593
latlng_to_mgrs(48.20535, 16.34593)
## [1] "33UXP0000040000"
mgrs_to_latlng("33UXP0500444996")
## mgrs lat lng
## 1 33UXP0500444996 48.24947 16.41449
latlng_to_mgrs(48.24948, 16.41449)
## [1] "33UXP0500344996"
mgrs_to_latlng("24XWT783908")
## mgrs lat lng
## 1 24XWT783908 83.62738 -32.66879
latlng_to_mgrs(83.62738, -32.66879)
## [1] "25XEN0410486507"
utm_to_mgrs(48, "N", 377299, 1483035)
## [1] "48PUV7729983035"
mgrs_to_utm("48PUV7729883034")
## mgrs zone hemisphere easting northing
## 1 48PUV7729883034 48 N 377298 1483034
ups_to_mgrs("N", 2426773, 1530125)
## [1] "ZGC2677330125"
mgrs_to_ups("ZGC2677330125")
## mgrs hemisphere easting northing
## 1 ZGC2677330125 N 2426773 1530125
grefs <- c("4Q", "4QFJ", "4QFJ16", "4QFJ1267", "4QFJ123678",
"4QFJ12346789", "4QFJ1234567890")
mgrs_precision(grefs)
## # A tibble: 7 x 2
## grid_ref precision
## <chr> <dbl>
## 1 4Q NA
## 2 4QFJ 100000
## 3 4QFJ16 10000
## 4 4QFJ1267 1000
## 5 4QFJ123678 100
## 6 4QFJ12346789 10
## 7 4QFJ1234567890 1Better usage in the {tidyverse}
data.frame(
id = 1:50,
mgrs = c("16SEB20", "09UXQ25", "12SVC48", "15SWU64", "11SKA54", "13SDC58",
"18TYM20", "18SWH08", "17RML38", "17SKR77", "09RYR61", "12TTP62",
"16TBK93", "16TEK73", "15TVG64", "14SNH75", "16SFG94", "15RWP68",
"19TEL05", "18SUJ54", "19TBG89", "16TFN87", "15TUM73", "16SBB31",
"15SWC44", "12TXS28", "14TML57", "11SND12", "19TCJ00", "18SWK62",
"13SDU11", "18TVN87", "17SQV22", "14TMT13", "17TLE65", "14SPE73",
"10TGP36", "18TTL93", "19TCG20", "17SNT42", "14TMQ40", "16SEE44",
"14RNV27", "12SVJ72", "18TXQ90", "17SQB46", "11TKN95", "17SNC25",
"16TBQ64", "13TCH16"),
stringsAsFactors = FALSE
) -> sample_dta
dplyr::mutate(sample_dta, x = lapply(mgrs, mgrs_to_latlng, include_mgrs_ref = FALSE)) %>%
tidyr::unnest(x)
## id mgrs lat lng
## 1 1 16SEB20 32.53717 -86.78701
## 2 2 09UXQ25 49.19105 -127.35303
## 3 3 12SVC48 34.15921 -111.65093
## 4 4 15SWU64 34.70027 -92.34486
## 5 5 11SKA54 36.47270 -119.79027
## 6 6 13SDC58 38.66717 -105.57474
## 7 7 18TYM20 41.52143 -72.36334
## 8 8 18SWH08 38.66858 -75.00000
## 9 9 17RML38 27.84288 -81.71090
## 10 10 17SKR77 32.24313 -83.44116
## 11 11 09RYR61 31.69589 -126.25687
## 12 12 12TTP62 43.49440 -113.96832
## 13 13 16TBK93 39.99409 -89.45983
## 14 14 16TEK73 40.01730 -86.17974
## 15 15 15TVG64 41.91094 -93.48232
## 16 16 14SNH75 38.39548 -98.19839
## 17 17 16SFG94 37.38730 -84.85379
## 18 18 15RWP68 30.55091 -92.37442
## 19 19 19TEL05 45.60354 -69.00000
## 20 20 18SUJ54 39.19632 -76.73702
## 21 21 19TBG89 42.33117 -71.67024
## 22 22 16TFN87 43.06136 -84.78947
## 23 23 15TUM73 46.31111 -94.68838
## 24 24 16SBB31 32.59461 -89.87671
## 25 25 15SWC44 38.30721 -92.54249
## 26 26 12TXS28 46.76276 -109.42851
## 27 27 14TML57 41.27989 -99.59705
## 28 28 11SND12 39.02899 -116.88447
## 29 29 19TCJ00 43.32625 -71.46678
## 30 30 18SWK62 39.92798 -74.29783
## 31 31 13SDU11 34.42756 -105.97949
## 32 32 18TVN87 43.08245 -75.24570
## 33 33 17SQV22 35.39912 -78.57750
## 34 34 14TMT13 47.21732 -100.18865
## 35 35 17TLE65 40.18872 -82.64462
## 36 36 14SPE73 35.49902 -97.12568
## 37 37 10TGP36 43.85725 -120.13815
## 38 38 18TTL93 40.89416 -77.49288
## 39 39 19TCG20 41.53142 -71.15763
## 40 40 17SNT42 33.61904 -80.56877
## 41 41 14TMQ40 44.25077 -99.75154
## 42 42 16SEE44 35.60294 -86.55839
## 43 43 14RNV27 31.36434 -98.78970
## 44 44 12SVJ72 39.02853 -111.34659
## 45 45 18TXQ90 44.22846 -72.62103
## 46 46 17SQB46 37.55578 -78.28300
## 47 47 11TKN95 47.36969 -119.78156
## 48 48 17SNC25 38.39800 -80.77096
## 49 49 16TBQ64 44.57333 -90.02272
## 50 50 13TCH16 42.96895 -107.32983Visual Verification
library(purrr)
library(ggplot2)
# precision == 1
c("16SEB20", "09UXQ25", "12SVC48", "15SWU64", "11SKA54", "13SDC58",
"18TYM20", "18SWH08", "17RML38", "17SKR77", "09RYR61", "12TTP62",
"16TBK93", "16TEK73", "15TVG64", "14SNH75", "16SFG94", "15RWP68",
"19TEL05", "18SUJ54", "19TBG89", "16TFN87", "15TUM73", "16SBB31",
"15SWC44", "12TXS28", "14TML57", "11SND12", "19TCJ00", "18SWK62",
"13SDU11", "18TVN87", "17SQV22", "14TMT13", "17TLE65", "14SPE73",
"10TGP36", "18TTL93", "19TCG20", "17SNT42", "14TMQ40", "16SEE44",
"14RNV27", "12SVJ72", "18TXQ90", "17SQB46", "11TKN95", "17SNC25",
"16TBQ64", "13TCH16") -> mgrs_state_centers
mgrs_to_latlng(mgrs_state_centers) %>%
ggplot(aes(lng, lat)) +
geom_point(shape=22, size=2, color="black", fill="white") +
coord_map("polyconic") +
theme_ft_rc(grid="XY")
