kdestimate: Kernel density estimation for spatial point pattern

In petrpajdla/settlements: Compendium accompanying article on settlement patters in the Neolithic period.

Kernel density estimation for spatial point pattern

Description

Wrapper around spatstat functions. Kernel density is estimated for a point pattern in a given window for different levels of a categorical variable.

Usage

kdestimate(x, mask, markscol, lvls, sigma = 4000, points = TRUE)

Arguments

x	sf object of geometry type POINTS in projected CRS.
mask	Single sf polygon, the study window.
markscol	Column name of x to use as grouping variable.
lvls	Vector of levels of markscol.
sigma	Standard deviation of isotropic smoothing kernel. Numeric value, passed to spatstat::density.splitppp function. Scale depends on coordinate reference system, for S-JTSK (EPSG 5514) it is in meters and defaults to 4 km.
points	Logical, return value for points or whole surface as raster image. Defaults to TRUE.

Value

With points set to TRUE (default) returns a tibble with KDE estimated at given points. If set to FALSE, a tibble with KDE values in a grid is returned to be plotted using ggplot2.

petrpajdla/settlements documentation built on June 27, 2022, 10:21 p.m.