Skip to contents

Path of water flow across a landscape

Source: R/flowPath.r
flowPath.Rd

This function finds the least-cost pathway from a set of starting points to the lowest cells accessible from them while, in each step, traversing "down" slope gradients. It is intended to depict the path a drop of water would take when flowing across a landscape. For a single starting point, the defaults settings will produce a raster with cells with values of 1 along the path. All other cells will be set to NA.

Usage

# S4 method for class 'GRaster'
flowPath(x, y, return = "ID")

Arguments

x

A GRaster with a single layer, typically representing elevation.

y

A "points" GVector. The GVector must have <= 1024 points.

return

Character: Indicates the type of values "burned" into the cells of the output raster. Case is ignored and partial matching is used, but only one option can be selected.

  • "ID" (default): Cells in each path are labeled with the index of the starting point. A cell in the flow path of the first point will have a value of 1, a cell in the flow path of the second point will have a value of 2, and so on.

  • "sequence": The output raster's cells will start with 1 at the source point(s), then accumulate so that the next cell in the flow path is 2, the one after that 3, and so on.

  • "copy": The cells in the flow path will have the elevation raster's values in the cells along the flow path(s).

  • "accumulation": Cells in the flow path will accumulate the elevation raster's cell values. For example, if the starting cell has an elevation of 700 and the next cell in the drainage path has a value of 600 and the one after that 500, then the first cell in the path will have a value of 700, the next 1300 (= 700 + 600), and the third 1800 (= 700 + 600 + 500).

  • A numeric value: All cells in flow paths will be assigned this value.

Value

A GRaster.

See also

flow(), streams(), the r.drain module for GRASS

Examples

if (grassStarted()) {

# Setup
library(terra)

# Example data
madElev <- fastData("madElev")
madCoast4 <- fastData("madCoast4")

# Convert to GRaster and crop to a sub-portion (easier for visualizing)
elev <- fast(madElev)
coast4 <- fast(madCoast4)
ant <- coast4[coast4$NAME_4 == "Antanambe"]
elevAnt <- crop(elev, ant)

# Create a set of random points to serve as starting points:
starts <- spatSample(elevAnt, 10, as.points = TRUE, seed = 1)

# Remove points in water:
starts <- starts[complete.cases(starts)]

# Calculate flow paths and label each by ID:
paths <- flowPath(elevAnt, starts)
paths

plot(paths)
plot(starts, pch = 1, add = TRUE)

# Calculate flow paths with cell values indicating the number
# of cells from each start:
seqs <- flowPath(elevAnt, starts, return = "seq")

plot(seqs)
plot(starts, pch = 1, add = TRUE)

# We can convert flow paths to lines:
seqLines <- as.lines(seqs)
plot(seqLines)
seqLines

}