#' compute tree metrics for list of LAS objects (should be normalized clouds, with buffer around area of interest). Call the treedetection function on each object and then arranges the results in a data.frame
#' Computation of tree metrics
#'
#' This function performs tree detection in each of LAS objects contained in a list and then computes summary statistics based on compute tree metrics for list of LAS objects (should be normalized clouds, with buffer around area of interest).
#' - calls the tree detection and extraction functions on each object
#' - remove the detected trees located outside of the regions of interest defined by their centers and radius
#' - computes summary statistics of remaining detected trees.
#'
#'
#' @param llasn list of LAS objects (from lidR package)
#' @param llasn list of LAS objects (from lidR package)
#' @param XY a dataframe or matrix with XY coordinates of plot centers
#' @param XY a dataframe or matrix with XY coordinates of plot centers
#' @param plot.radius a numeric plot radius in m
#' @param plot.radius numeric. plot radius in same unit as coordinates of LAS objects
#' @param res CHM resolution for tree detection (m)
#' @param res numeric. resolution of canopy height model computed with \code{\link{points2DSM}} before tree segmentation
#' @param hmin min height for a tree (m)
#' @param h.points height for CHM thresholding (m)
#' @param func a function to be applied to the attributes of extracted trees (return from internal call to treeExtraction function to compute plot level metrics
#' @param func a function to be applied to the attributes of extracted trees (return from internal call to treeExtraction function to compute plot level metrics
#' @param ... other parameters to be passed to \code{\link{treeSegmentation}}
#' @return a dataframe with tree metrics in columns corresponding to LAS objects of the list (lines)
#' @return a dataframe with tree metrics in columns corresponding to LAS objects of the list (lines)
cloudTreeMetrics(llasn, XY, plot.radius, res = 0.5,
func = stdTreeMetrics, ...)
}
\arguments{
\item{llasn}{list of LAS objects (from lidR package)}
\item{XY}{a dataframe or matrix with XY coordinates of plot centers}
\item{plot.radius}{numeric. plot radius in same unit as coordinates of LAS objects}
\item{res}{numeric. resolution of canopy height model computed with \code{\link{points2DSM}} before tree segmentation}
\item{func}{a function to be applied to the attributes of extracted trees (return from internal call to treeExtraction function to compute plot level metrics}
\item{...}{other parameters to be passed to \code{\link{treeSegmentation}}}
}
\value{
a dataframe with tree metrics in columns corresponding to LAS objects of the list (lines)
}
\description{
This function performs tree detection in each of LAS objects contained in a list and then computes summary statistics based on compute tree metrics for list of LAS objects (should be normalized clouds, with buffer around area of interest).
- calls the tree detection and extraction functions on each object
- remove the detected trees located outside of the regions of interest defined by their centers and radius
- computes summary statistics of remaining detected trees.
