R: Kernel Smoothing of Linear Network

density.linnet {spatstat.linnet} | R Documentation

## Kernel Smoothing of Linear Network

### Description

Compute a kernel smoothed intensity function for the line segments of a linear network.

### Usage

      ## S3 method for class 'linnet'
    density(x, ...)

### Arguments

`x` | Linear network (object of class `"linnet"`)
`...` | Arguments passed to `density.psp` to control the amount of smoothing and the spatial resolution of the result.

### Details

This is the method for the generic function `density` for the class `"linnet"` (linear networks).

The network `x` is first converted to a line segment pattern (object of class `"psp"`). Then the method `density.psp` is applied to the segment pattern.

A kernel estimate of the intensity of the line segment pattern is computed. The result is the convolution of the isotropic Gaussian kernel, of standard deviation `sigma`, with the line segments.

The intensity of a line segment pattern is the (spatially-varying) amount of segment length per unit area, expressed in the same units as the coordinates of `x`. If the units of `x` are in metres, then an intensity value of 3 means that there are 3 metres of segment length per square metre of spatial domain.

See `density.psp` for more details.

### Value

A pixel image in two dimensions (object of class `"im"`) or a numeric vector.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.

### See Also

`density.psp`, `im.object`, `density`.

### Examples

      D <- density(simplenet, 0.1)
      plot(D)
      plot(simplenet, add=TRUE, col="white")
      ## compare with average intensity
      volume(simplenet)/area(Window(simplenet))

[Package spatstat.linnet version 2.0-0 Index]