" class="reference-link">smoothr

smoothr offers a variety of tools for smoothing and tidying spatial
features (i.e. polygons and lines) to make them more aesthetically
pleasing, especially when converting raster data to vector format. This
package offers support for both sp and sf spatial objects. The
following smoothing methods are available:

• Chaikin’s corner cutting algorithm: smoothing using Chaikin’s
  corner cutting algorithm, which iteratively replaces every point by
  two new points: one 1/4 of the way to the next point and one 1/4 of
  the way to the previous point. This method applies a moderate amount
  of smoothing of sharp corners without extensive generalization.
• Kernel smoothing: smoothing using Gaussian kernel regression via
  the ksmooth() function. This approach first densifies the feature
  (i.e. adds more vertices) then applies the kernel smoothing. Kernel
  smoothing simultaneously smooths and generalizes curves, and can be
  tuned to produce extensively smoothed curves.
• Spline interpolation: smoothing using spline interpolation via
  the spline() function. This method interpolates between existing
  vertices and should be used when the resulting smoothed feature must
  pass through the vertices of the input feature.

In addition to these smoothing functions, smoothr offers functions for
filling polygon holes and dropping line and polygon fragments based on a
size threshold, as well as densification (i.e. adding additional
vertices along curves).

When using smoothr, a couple important warnings should be
considered: 1. Smoothing can give the false perception of higher
precision than actually exists in the data, so users should be cautious
when applying these algorithms. 2. The smoothing algorithms used do not
preserve topological boundaries between features, therefore this package
is not suitable for smoothing isolines (e.g. elevation contours) or
administrative boundaries (e.g. country borders)

Installation

# install from cran with
install.packages("smoothr")
# or install the development version from github with
# install.packages("devtools")
devtools::install_github("mstrimas/smoothr")

Usage

Two example feature sets are included in this package. jagged_polygons
contains 9 polygons with sharp edges for smoothing, some have holes and
some are multipart polygons. We can smooth these using the different
methods available and plot a comparison:

library(sf)
library(smoothr)
par(mar = c(0, 0, 0, 0), oma = c(4, 0, 0, 0), mfrow = c(3, 3))
p_smooth_chaikin <- smooth(jagged_polygons, method = "chaikin")
p_smooth_ksmooth <- smooth(jagged_polygons, method = "ksmooth")
p_smooth_spline <- smooth(jagged_polygons, method = "spline")
for (i in 1:nrow(jagged_polygons)) {
  plot(st_geometry(p_smooth_spline[i, ]), col = NA, border = NA)
  plot(st_geometry(jagged_polygons[i, ]), col = "grey40", border = NA, add = TRUE)
  plot(st_geometry(p_smooth_chaikin[i, ]), col = NA, border = "#E41A1C", lwd = 2, add = TRUE)
  plot(st_geometry(p_smooth_ksmooth[i, ]), col = NA, border = "#4DAF4A", lwd = 2, add = TRUE)
  plot(st_geometry(p_smooth_spline[i, ]), col = NA, border = "#377EB8", lwd = 2, add = TRUE)
}
par(fig = c(0, 1, 0, 1), oma = c(0, 0, 0, 0), new = TRUE)
plot(0, 0, type = "n", bty = "n", xaxt = "n", yaxt = "n", axes = FALSE)
legend("bottom", legend = c("chaikin", "ksmooth", "spline"),
       col = c("#E41A1C", "#4DAF4A", "#377EB8"),
       lwd = 2, cex = 2, box.lwd = 0, inset = 0, horiz = TRUE)

jagged_lines contains 9 lines with sharp edges for smoothing, some are
closed loops requiring special treatment of the endpoints and some are
multipart lines. For variety, let’s smooth these using spline
interpolation:

par(mar = c(0, 0, 0, 0), oma = c(4, 0, 0, 0), mfrow = c(3, 3))
l_smooth_chaikin <- smooth(jagged_lines, method = "chaikin")
l_smooth_ksmooth <- smooth(jagged_lines, method = "ksmooth")
l_smooth_spline <- smooth(jagged_lines, method = "spline")
for (i in 1:nrow(jagged_lines)) {
  plot(st_geometry(l_smooth_spline[i, ]), col = NA)
  plot(st_geometry(jagged_lines[i, ]), col = "grey20", lwd = 3, add = TRUE)
  plot(st_geometry(l_smooth_chaikin[i, ]), col = "#E41A1C", lwd = 2, lty = 2, add = TRUE)
  plot(st_geometry(l_smooth_ksmooth[i, ]), col = "#4DAF4A", lwd = 2, lty = 2, add = TRUE)
  plot(st_geometry(l_smooth_spline[i, ]), col = "#377EB8", lwd = 2, lty = 2, add = TRUE)
}
par(fig = c(0, 1, 0, 1), oma = c(0, 0, 0, 0), new = TRUE)
plot(0, 0, type = "n", bty = "n", xaxt = "n", yaxt = "n", axes = FALSE)
legend("bottom", legend = c("chaikin", "smooth", "spline"),
       col = c("#E41A1C", "#4DAF4A", "#377EB8"),
       lwd = 2, cex = 2, box.lwd = 0, inset = 0, horiz = TRUE)

Other goodies

smoothr contains a handful of other tools to help clean up spatial
features and make them look cleaner and more aesthetically pleasing.

• densify() (and it’s alias smooth(x, method = "densify"))
  densifies lines and polygons, adding additional vertices along line
  segments.
• drop_crumbs() removes small lines or polygons based on a length or
  area threshold.
• fill_holes() fills (i.e. removes) holes from polygons when they
  are below a given area threshold.

See the documentation for these functions for full details.

Code of Conduct

Please note that this project is released with a Contributor Code of
Conduct. By participating in this project you agree
to abide by its terms.

Contributing

To contribute to the development of this project please refer to the
guidelines.