slope_vector() calculates the slopes associated with consecutive elements in one dimensional distance and associated elevations (see examples).

slope_distance() calculates the slopes associated with consecutive distances and elevations.

slope_distance_mean() calculates the mean average slopes associated with consecutive distances and elevations.

slope_distance_weighted() calculates the slopes associated with consecutive distances and elevations, with the mean value associated with each set of distance/elevation vectors weighted in proportion to the distance between each elevation measurement, so longer sections have proportionally more influence on the resulting gradient estimate (see examples).

slope_vector(x, elevations)

slope_distance(d, elevations)

slope_distance_mean(d, elevations, directed = FALSE)

slope_distance_weighted(d, elevations, directed = FALSE)

## Arguments

x Vector of locations Elevations in same units as x (assumed to be metres) Vector of distances between points Should the value be directed? FALSE by default. If TRUE the result will be negative when it represents a downslope (when the end point is lower than the start point).

## Value

A vector of slope gradients associated with each linear element (each line between consecutive vertices) associated with linear features. Returned values for slope_distance_mean() and slope_distance_mean_weighted() are summary statistics for all linear elements in the linestring. The output value is a proportion representing the change in elevation for a given change in horizontal movement along the linestring. 0.02, for example, represents a low gradient of 2% while 0.08 represents a steep gradient of 8%.

## Examples

x = c(0, 2, 3, 4, 5, 9)
elevations = c(1, 2, 2, 4, 3, 0) / 10 # downward slope overall
slope_vector(x, elevations)
#> [1]  0.050  0.000  0.200 -0.100 -0.075library(sf)
#> [1] -0.09501323