In tankwin08/waveformlidar: Waveform LiDAR Data Processing and Analysis

stopifnot(require(knitr))
options(width = 90)
opts_chunk$set(
  comment = NA,
  message = FALSE,
  warning = FALSE,
  eval = if (isTRUE(exists("params"))) params$EVAL else FALSE,
  dev = "png",
  dpi = 150,
  fig.asp = 0.8,
  fig.width = 5,
  out.width = "60%",
  fig.align = "center"
)
library(waveformlidar)
#ggplot2::theme_set(theme_default())

Goal

The purpose of this vignette is to show an example of converting waveforms into point cloud with high density (HPC). In addition, we also explore several applications of the HPC to demonstrate the usefulness of the products.

A Case Study

data(geo)
data(return)

geo$index<-NULL
colnames(geo)[1:8]<-c("x","y","z","dx","dy","dz","or","fr")
hpc<-hyperpointcloud(waveform=return,geo=geo)

large dataset

For a large data set, we need to use the data.table or rspark to deal with the big data frame the following code is just an example, you can adjust as your needs.

re<-NULL
chunks=5
row_interval<- round(seq(1,nrow(return),length.out = chunks))
for (i in 1:(chunks-1)){
  swf<-waveform[row_interval[i]:(row_interval[i+1]-1)]
  sgeo<-geo[row_interval[i]:(row_interval[i+1]-1)]
  sre<-hyperpointcloud(swf,sgeo)
  fwrite(sre,paste0("subset_hpc_",i,".csv"))
  re<-rbind(re,sre)
}

HPC explorations

hpcgrid<-waveformgrid(hpc=hpc,res=c(1,1))
###using raw data
rawgrid<-waveformgrid(waveform = return,geo=geo,method="Other")
##adding quantiles
quangrid<-waveformgrid(hpc=hpc,res=c(1,1),quan=c(0.4,0.48,0.58,0.67,0.75,0.85,0.95))
##for using the other method, we must assign the method
rquangrid<-waveformgrid(waveform = return,geo = geo,res=c(1,1),quan=c(0.4,0.48,0.58,0.67,0.75,0.85,0.95),method="Other")

####waveformvoxel
voxr<-waveformvoxel(hpc,res=c(1,1,0.15))
##adding quan
qvoxr<-waveformvoxel(hpc,res=c(1,1,0.15),quan=c(0.4,0.5,0.75,0.86))

###convert the hpc to the composite waveforms
rtc<-rawtocomposite(voxr)
###from hyper point cloud to composite waveforms, the inten_index will determine which intensity variable of the voxel you will use
ph_rtc<-rawtocomposite(qvoxr,inten_index = 6)