The goal of this vignette is to demonstrate how to pull the
stream network associated with a waterbody catchment. We will use the
extract_network
function to accomplish this task using the
built-in mendota
dataset.
Let’s start by pulling the coordinates associated with Lake Mendota, which will be the largest object (by area) in the waterbody object.
data(mendota)
largest_waterbody <- which.max(st_area(mendota$sp$NHDWaterbody))
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
mendota_lake <- mendota$sp$NHDWaterbody[largest_waterbody, ]
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
mendota_lake <- st_transform(mendota_lake, crs = 4326)
mendota_centroid <- st_coordinates(st_centroid(mendota_lake))
Next, we can use the extract_network
function to pull
the stream network associated with Lake Mendota. Notice that we have set
the maxsteps
parameter to Inf. If the
network is anticipated to be very large it can be a good idea to set
this to a discrete (lower) number to avoid returning very large lines
objects.
mendota_network <- extract_network(lon = mendota_centroid[1],
lat = mendota_centroid[2],
maxsteps = Inf)
Finally, we compare the stream network from a geometric buffer around
Lake Mendota against the output of extract_network
to make
sure everything is working properly.
ggplot() +
geom_sf(data = mendota$sp$NHDFlowLine) +
geom_sf(data = mendota_lake, fill = "cyan") +
geom_sf(data = mendota_network, color = "blue")
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()
#> old-style crs object detected; please recreate object with a recent sf::st_crs()