R: Compute metrics for a cloud of points

cloud_metrics {lidR} | R Documentation

## Compute metrics for a cloud of points

### Description

`cloud_metrics` computes a series of user-defined descriptive statistics for a LiDAR dataset. See grid_metrics to compute metrics on a grid. Basically there are no predefined metrics. Users must write their own functions to create metrics (see example). The following existing functions can serve as a guide to help users compute their own metrics:

- stdmetrics

- entropy

- VCI

- LAD

### Usage

    cloud_metrics(las, func)

### Arguments

`las` | An object of class `LAS`
`func` | formula. An expression to be applied to the point cloud (see example)

### Value

It returns a `list` containing the metrics

### See Also

grid_metrics stdmetrics entropy VCI LAD

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

### Examples

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

    cloud_metrics(lidar, ~max(Z))
    cloud_metrics(lidar, ~mean(Intensity))

    # Define your own new metrics
    myMetrics = function(z, i)
    {
      metrics = list(
         zwimean = sum(z*i)/sum(i), # Mean elevation weighted by intensities
         zimean  = mean(z*i),       # Mean products of z by intensity
         zsqmean = sqrt(mean(z^2))  # Quadratic mean
       )

       return(metrics)
    }

    metrics = cloud_metrics(lidar, ~myMetrics(Z, Intensity))

    # Predefined metrics
    cloud_metrics(lidar, .stdmetrics)

[Package lidR version 3.2.2 Index]