README.md

remr

The goal of remr is to get transects along a linestring so that you can then perform a Relative Elevation Model. Thanks to paleolimbot this process is now in a function!

Contributions

Contributions are welcome! Please if you have any ideas or recommendations submit an issue. Thanks.

Installation

To install the development version of the remr package, you can install directly from GitHub:

# install.packages("devtools")
devtools::install_github("joshualerickson/remr")

Example

This is a basic example which shows you how to solve a common problem: getting transects along a linestring and then extracting points on the linestring and transects.

library(remr)
library(dplyr)

pts = matrix(c(170800,172000, 5410500, 5410400), 2)
line = sf::st_as_sf(sf::st_sfc(sf::st_linestring(pts), crs = 32612))

ele <- elevatr::get_elev_raster(line, z = 13, prj = '+proj=utm +zone=12 +datum=WGS84 +units=m +no_defs')

rem <- get_rem(line, ele, distance = 100, length = 500)

 ele_crop <- terra::crop(terra::rast(ele), terra::vect(sf::st_buffer(line, 200)))
 terra::plot(ele_crop)
 plot(line$x, add = TRUE)
 plot(rem$geometry, add = TRUE)

 
#get resolution to make more points
res <- terra::res(ele)
rem <- get_rem(line, ele, distance = res[[1]], length = 500)


#now convert to raster
rem_rast <- rem_raster(rem, ele_crop, fun = 'mean', window = 3, na.rm = TRUE)

terra::plot(rem_rast)
plot(line, add = TRUE)

 
transects <- get_transects(line, distance = 100, length = 500)

terra::plot(ele_crop)
plot(transects, add = TRUE)

 
points <- get_transect_points(line, distance = 100, length = 500)

terra::plot(ele_crop)
plot(points, add = TRUE)

#use nhdplus to get streams

pt <- sf::st_as_sf(sf::st_sfc(sf::st_point(c(-115.074062, 48.741195))), crs = 4326) %>% 
                         dplyr::rename(geometry = 'x')

streams <- gwavr::get_NLDI(pt)
#> [1] "site_data is of class sf and has 1 features"        
#> [2] "site_data is of class tbl_df and has 1 features"    
#> [3] "site_data is of class tbl and has 1 features"       
#> [4] "site_data is of class data.frame and has 1 features"
#> [1] "basin_boundary is of class sf and has 1 features"        
#> [2] "basin_boundary is of class tbl_df and has 1 features"    
#> [3] "basin_boundary is of class tbl and has 1 features"       
#> [4] "basin_boundary is of class data.frame and has 1 features"
#> [1] "UT is of class sf and has 28 features"        
#> [2] "UT is of class tbl_df and has 28 features"    
#> [3] "UT is of class tbl and has 28 features"       
#> [4] "UT is of class data.frame and has 28 features"
#> [1] "UM is of class sf and has 11 features"        
#> [2] "UM is of class tbl_df and has 11 features"    
#> [3] "UM is of class tbl and has 11 features"       
#> [4] "UM is of class data.frame and has 11 features"
ut <- streams$UT %>% sf::st_transform(32612)
ele <- elevatr::get_elev_raster(ut[1:5,], z = 13, prj = '+proj=utm +zone=12 +datum=WGS84 +units=m +no_defs')

# run in parallel

bm_rem <- microbenchmark::microbenchmark(
  'normal' = ut[1:5,] %>% 
  split(.$nhdplus_comid) %>%  
  purrr::map(~get_rem(., ele, terra::res(ele)[[1]], 500)),
  'parallel'  = {
    library(future)
    plan(multisession(workers = availableCores()-1))
    ut[1:5,] %>% 
  split(.$nhdplus_comid) %>%  
  furrr::future_map(~get_rem(., ele,  terra::res(ele)[[1]], 500))
  }, times = 5
)

ggplot2::autoplot(bm_rem) + 
  ggplot2::labs(title = '5 NHDPLUS COMIDs (5 times each)') +
  ggplot2::theme_bw()

Below is a quick workflow to REMs

# get elevations for each transect using rem

pinkam <- ut[1:5,] %>% 
  split(.$nhdplus_comid) %>%  
  furrr::future_map(~get_rem(., ele,  terra::res(ele)[[1]], 500))

# As of 2/9/2022 future_map crashes with one of the functions in rem_raster(), sorry...
pinkham_rast <- pinkam[c(ut[1:5,]$nhdplus_comid)] %>% 
                 purrr::map(~rem_raster(.,ele, na.rm = TRUE))

raa_tog <- terra::sprc(pinkham_rast)
t <- terra::mosaic(raa_tog)

t_crop <- terra::crop(t, sf::st_buffer(ut[1:5,], 200))
terra::plot(t_crop)
plot(ut[1:5,]$geometry, add = TRUE)