R: Voxelize the space and compute metrics for each voxel

voxel_metrics {lidR} | R Documentation

## Voxelize the space and compute metrics for each voxel

### Description

This is a 3D version of grid_metrics. It creates a 3D matrix of voxels with a given resolution. It creates a voxel from the cloud of points if there is at least one point in the voxel. For each voxel the function allows computation of one or several derived metrics in the same way as the grid_metrics functions. The function will dispatch the LiDAR data for each voxel in the user's function (see grid_metrics).

### Usage

    voxel_metrics(las, func, res = 1, ..., all_voxels = FALSE)

### Arguments

`las` | An object of class `LAS`.
`func` | formula. An expression to be applied to each voxel (see also grid_metrics).
`res` | numeric. The resolution of the voxels. `res = 1` for a 1x1x1 cubic voxels. Optionally `res = c(1,2)` for non-cubic voxels (1x1x2 cuboid voxel).
`...` | Unused
`all_voxels` | boolean. By default the function returns only voxels that contain 1 or more points. Empty voxels do not exist as the metrics are undefined. If `all_voxels = TRUE` all the voxels are returned and metrics are NA for voxels with 0 points.

### Value

It returns a `data.table` containing the metrics for each voxel. The table has the class `lasmetrics3d` enabling easier plotting. It also has an attribute `res` that stores the resolution.

### See Also

Other metrics: `cloud_metrics()`, `grid_metrics()`, `plot_metrics()`, `point_metrics()`, `tree_metrics()`

### Examples

    LASfile <- system.file("extdata", "Megaplot.laz", package="lidR")
    las <- readLAS(LASfile)

    # Cloud of points is voxelized with a 8-meter resolution and in each voxel
    # the number of points is computed.
    vm <- voxel_metrics(las, ~length(Z), 8)

    # Cloud of points is voxelized with a 8-meter resolution and in each voxel
    # the mean intensity of points is computed.
    vm <- voxel_metrics(las, ~mean(Intensity), 8)
    #plot(vm, color = "V1", colorPalette = heat.colors(50), trim = 60)

    # Define your own metric function
    myMetrics = function(i)
    {
      ret = list(
         npoints = length(i),
         imean   = mean(i)
       )

       return(ret)
    }

    voxels <- voxel_metrics(las, ~myMetrics(Intensity), 8)

    #plot(voxels, color = "imean", colorPalette = heat.colors(50), trim = 60)
    #etc.

    attr(voxels, "res")

[Package lidR version 3.2.2 Index]