lidR (version 2.2.1)

cloud_metrics: 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(), hexbin_metrics(), point_metrics(), tree_metrics(), voxel_metrics()

Examples

# NOT RUN {
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)
# }