rrrem

rrrem is an R port of the RiverREM package, letting you use packages in R’s spatial programming ecosystem to produce relative elevation models. Specifically, this package implements the river-retrieving and REM-producing elements of RiverREM; because R has such strong graphing support for raster graphics, the visualizations are not re-implemented (but are easily re-created using either base R or ggplot2).

Please note that this package was made extremely quickly and is effectively untested – there may be some sharp edges yet to be sanded down, and may be breaking changes on the horizon.

Installation

You can install the development version of rrrem like so:

remotes::install_github("mikemahoney218/rrrem")

Example

rrrem creates relative elevation models (REMs) based upon user-supplied digital elevation models (DEMs) and river locations optionally downloaded via OpenStreetMap. As such, in order to use rrrem, we first need to get a DEM.

We can get high-resolution DEMs for areas in the United States by using the sf and terrainr packages, like so:

dem <- sf::st_as_sf(
  data.frame(
    y = c(43.412402, 43.489347), 
    x = c(-123.591623, -123.479736)
  ),
  coords = c("x", "y"),
  crs = 4326
) |> 
  sf::st_transform(3857) |> 
  terrainr::get_tiles() |> 
  purrr::chuck("elevation") |> 
  terrainr::merge_rasters()

With our data downloaded, we’re ready to move on to actually using rrrem. The main workhorse of this package is the make_rem() function, which takes a DEM (and optionally, a line geometry reflecting your “target” river to visualize) and converts it into an REM. We can call that function like this:

library(rrrem)

rem <- make_rem(dem)

And, well, that’s more or less what the package does. Kinda an anti-climax, that.

Rather than re-implement the visualization helpers from the RiverREM package, rrrem returns data in formats that the R spatial and visualization ecosystems will recognize, making it easy for users to hyper-customize their visualizations without needing to learn a new plotting function. For instance, the rem object we just created can be plotted quickly via terra::plot():

terra::plot(rem)

Or, with a little more elbow grease, we can combine it with other functions from terra to make more customizable visualizations:

dem <- terra::rast(dem)

hillshade <- terra::shade(
  terra::terrain(dem, "slope", unit = "radians"),
  terra::terrain(dem, "aspect", unit = "radians")
)

trimmed_rem <- rem
trimmed_rem[trimmed_rem > 200] <- 200

par(
  oma = c(0, 0, 0, 0),
  mar = c(0, 0, 0, 0),
  mgp = c(0, 0, 0)
)


terra::plot(
  hillshade, 
  col = grey(0:100/100), 
  legend = FALSE, 
  axes = FALSE,
  oma = NA,
  mar = NA,
  xaxs="i", 
  yaxs="i"
)


terra::plot(
  trimmed_rem,
  col = viridis::mako(50, direction = -1), 
  legend = FALSE, 
  axes = FALSE,
  add = TRUE,
  alpha = 0.75
)

Code of Conduct

Please note that the rrrem project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.