Description Usage Arguments Value References Examples
View source: R/decom.adaptive.R
The function allows you to eatimate parameters charcterizing waveforms and to pave the way for generating waveform-based point cloud.
1 | decom.adaptive(x, smooth = TRUE, thres = 0.22, width = 3)
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x |
is a waveform with a index at the begining and followed with intensities. |
smooth |
is tell whether you want to smooth the waveform to remove some obvious outliers. Default is TRUE. |
thres |
is to determine if the detected peak is the real peak whose intensity should be higher than threshold*maximum intensity. Default is 0.22. |
width |
width of moving window.Default is 3, must be odd integer between 1 and n.This parameter ONLY work when the smooth is TRUE. |
A list contains estimates of A, u, sig and ri (rate parameter in adaotive Gaussian function) after decomposition.
Tan Zhou, and Sorin C. Popescu, 2017. Bayesian decomposition of full waveform LiDAR data with uncertainty analysis. Remote Sensing of Environment 200 (2017): 43-62.
1 2 3 4 5 6 7 8 9 10 11 12 13 | ##import return waveform data
data(return)
lr<-nrow(return)
ind<-c(1:lr)
return<-data.frame(ind,return)
x<-return[1,] ###must be a dataset including intensity with index at the beginning.
r1<-decom(x)
r2<-decom.adaptive(x)
# for the whole dataset
dr3<-apply(return[50:200, ],1,decom.adaptive)
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