The goal of reproj is to reproject data between coordinate systems.
The basic function reproj()
takes input in diverse forms (matrix, data
frame) and returns a 3-column matrix, by transforming from map
projection specfied by the source
argument to that specified by the
target
argument.
The functions reproj_xy()
and reproj_xyz()
drive the underlying
reproj()
for those specific cases for convenience.
We cannot currently do time-dependent transformations.
Matrix and data frame is the basic data structure in R, and this model
also allows adding methods for specific data formats that already carry
a suitable source
projection string. Currently we support types from
the silicate and quadmesh and rgl packages, and only the target
string
need be specified. This model has obvious flexibility, for packages to
import the generic and call it with the correct source
(from the data
format) and the target
from user, or process controlled mechanism.
The source
argument must be named, and if it is not present a light
check is made that the source data could be “longitude/latitude” and
transformation to target
is applied (this can be controlled by setting
options).
Until recently the proj4
package was the only one available for
generic data that will transform between arbitrary coordinate systems
specified by source and target coordinate systems and with control
over ‘xy’ versus ‘xyz’ input and output. This package adds some further
features by wrapping the need to convert longitude/latitude data to or
from radians.
Other R packages for transforming coordinates are not geared toward data that’s not in a particular format. It’s true that only GDAL provides the full gamut of available geographic map projections, but this leaves a huge variety of workflows and applications that don’t need that level of functionality. sf and terra both have raw ‘project()’ functions but they have inconvenient interfaces, or don’t support some transformations or the return of missing values.
- The PROJ package is used preferentially if is functional, using the underlying ‘PROJ-lib’ at version 6 or higher.
- The proj4 package is used if PROJ is not functional.
The proj4 package works perfectly well with the PROJ-lib.
Whether a particular source->target transformation pathway is appropriate for your application is your responsibility.
You can install the dev version of reproj from github with:
remotes::install_github("hypertidy/reproj")
This example shows how to convert between coordinate systems:
library(reproj)
(pt <- (reproj(cbind(c(147, 148), c(-42, -45)), target = "+proj=laea +datum=WGS84", source = "OGC:CRS84")))
#> x_ y_
#> [1,] 5969744 -9803200 0
#> [2,] 5362760 -10052226 0
## to another coordinate system
(pt1 <- reproj(pt, target = "+proj=lcc +lat_1=-20 +lat_2=-10 +datum=WGS84", source = "+proj=laea +datum=WGS84"))
#> x_ y_ z_
#> [1,] 12701201 -9158714 0
#> [2,] 12538357 -9514556 0
## and back again
reproj(pt1, target = "OGC:CRS84", source = "+proj=lcc +lat_1=-20 +lat_2=-10 +datum=WGS84")
#> x_ y_ z_
#> [1,] 147 -42 0
#> [2,] 148 -45 0
Note that the output is always in ‘xyz’ form, even if the z value is implied zero. The input may also be ‘xyz’ and it is the user’s job to ensure this is specified correctly. It’s not possible to automate every case, because among the three main cases:
- longitude latitude and elevation,
- projected xy and elevation,
- geocentric xyz with embedded elevation (an offset to the radius
+a/+b
in PROJ terms),
it is not possible to easily capture the intended task. reproj sits at the simplest level of flexibility and control, and doesn’t impose any restrictions of converting between these cases.
Are you interested in reproj or even contributing? Great! Please use the issues tab for discussions.
This is a wishlist / todo.
- see libproj make it to CRAN for the long term
Please note that the ‘reproj’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.