waveformlidar (version 1.2.0)

rawtocomposite: rawtocomposite

Description

The function allows you to convert point cloud after waveformvoxel or raw waveforms into composite waveforms (with vertical distribution of intensity) by reducing the effect of off-naid angle of emitted laser. The conversion is based on the waveform voxellization product. Four kinds of values you can chose to represent the intensity of composite waveform: the number of intensity (generally is not useful), mean intensity, maximum intensity and total intensity (the last one is also not prefered in most of cases).

Usage

rawtocomposite(voxr, inten_index = 2)

Arguments

voxr

the object from the waveformvoxel.

inten_index

the value (1,2,3,4,...) to represnt the intensity of composite waveforms.It is a integer from 1 to 4 and default is 2. 1: the number of intensity of the voxel (generally is not useful); 2: the maximum intensity of the waveform voxel; 3: the mean intensity of the waveform voxel; 4: the total intensity of voxel(the last one is also not prefered in most cases)

Value

A dataframe with first three columns including geolocation xyz of the first Non-NA intensity (Highest position) and intensities along the height bins, other non-NA values are intensities for the rest columns.

x

The x position of the first Non-NA intensity or highest intensity position in one waveform

y

The y position of the first Non-NA intensity or highest intensity position in one waveform

z

The z position of the first Non-NA intensity or highest intensity position in one waveform

intensity 1

The intnesity of first height bin

intensity 2

The intensity of second height bin

...

Intensities along the height bin

Examples

# NOT RUN {
data(return)  ###import raw return waveforms
data(geo)  ###import corresponding reference geolocation
colnames(geo)[2:9]<-c("x","y","z","dx","dy","dz","or","fr")
### you should know which columns corresponding to above column names before
### run the hyperpointcloud when you used your own new datasets.

hpr<-hyperpointcloud(waveform=return,geo=geo)

##beofre run waveformvoxel, we need to create hyperpointcloud first
##this exampel we just used 100000 points to reduce processing time

voxr<-waveformvoxel(hpc=hpr,res=c(1,1,0.3))
rtc<-rawtocomposite(voxr)
# }