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.
Dependencies
- 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.
Warning
Whether a particular source->target transformation pathway is appropriate for your application is your responsibility.
Installation
You can install the dev version of reproj from github with:
remotes::install_github("hypertidy/reproj")Example
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 0Note 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/+bin 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.
Contributions
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.
