GEDI full waveform data simulation
Simulate GEDI full waveform data from Airborne Laser Scanning (ALS) 3D point cloud
Input and output filenames, and formats
gediWFSimulator( input, output, waveID = NULL, coords = NULL, listCoord = NULL, gridBound = NULL, gridStep = 30, pSigma = -1, pFWHM = 15, readPulse = NULL, fSigma = 5.5, wavefront = NULL, res = 0.15, topHat = FALSE, sideLobe = FALSE, lobeAng = 0, checkCover = FALSE, maxScanAng = 1e+06, decimate = 1, pBuff = as.integer(2e+08), maxBins = as.integer(1024), countOnly = FALSE, pulseAfter = FALSE, pulseBefore = TRUE, noNorm = FALSE, noOctree = FALSE, octLevels = as.integer(0), nOctPix = as.integer(40), keepOld = FALSE, useShadow = FALSE, polyGround = FALSE )
input |
character vector. lasfile input filename |
output |
character. output filename |
waveID |
id. supply a waveID to pass to the output (only for single footprints) Single footprint, list of footprints, or grid of footprints |
coords |
lon lat numeric vector. footprint coordinate in same system as lasfile |
listCoord |
name. Text file with list of coordinates. Pattern: X Y '[waveID]' '[geoCoordsX]' '[geoCoordsY]'. '[]' are optional, separated by spaces. |
gridBound |
minX maxX minY maxY numeric vector. make a grid of waveforms in this box |
gridStep |
res. grid step size Lidar characteristics. Defaults are expected GEDI values. |
pSigma |
pSigmasig. set Gaussian pulse width as 1 sigma |
pFWHM |
fhwm. set Gaussian pulse width as FWHM in ns |
readPulse |
file. read pulse shape and width from a file insteda of making Gaussian |
fSigma |
sig. set footprint width |
wavefront |
file. read wavefront shape from file instead of setting Gaussian. Note that footprint width is still set by fSigma |
res |
res. range resolution of waveform digitisation to output, in units of ALS data |
topHat |
use a top hat wavefront |
sideLobe |
use side lobes |
lobeAng |
ang. lobe axis azimuth Input data quality filters |
checkCover |
check that the footprint is covered by ALS data. Do not output if not |
maxScanAng |
ang. maximum scan angle, degrees |
decimate |
x. probability of accepting an ALS beam Computational speed options |
pBuff |
s. point reading buffer size in Gbytes |
maxBins |
for HDF5, limiting number of bins to save trimming. |
countOnly |
only use count method |
pulseAfter |
apply the pulse smoothing after binning for computational speed, at the risk of aliasing (default) |
pulseBefore |
apply the pulse smoothing before binning to avoid the risk of aliasing, at the expense of computational speed |
noNorm |
don't normalise for ALS density Octree |
noOctree |
do not use an octree |
octLevels |
n. number of octree levels to use |
nOctPix |
n. number of octree pixels along a side for the top level Using full waveform input data (not tested) |
keepOld |
do not overwrite old files, if they exist |
useShadow |
account for shadowing in discrete return data through voxelization |
polyGround |
find mean ground elevation and slope through fitting a polynomial #' |
Returns an S4 object of class hdf5r::H5File form the hdf5r package
containing the simulated GEDI full-waveform.
i) Hancock, S., Armston, J., Hofton, M., Sun, X., Tang, H., Duncanson, L.I., Kellner, J.R. and Dubayah, R., 2019. The GEDI simulator: A large-footprint waveform lidar simulator for calibration and validation of spaceborne missions. Earth and Space Science. https://doi.org/10.1029/2018EA000506
ii) gediSimulator: https://bitbucket.org/StevenHancock/gedisimulator/src/master/
libsAvailable = require(lidR) && require(plot3D)
if (libsAvailable) {
outdir=tempdir()
# specify the path to ALS data (zip)
alsfile_Amazon_zip <- system.file("extdata", "Amazon.zip", package="rGEDI")
alsfile_Savanna_zip <- system.file("extdata", "Savanna.zip", package="rGEDI")
# Unzipping ALS data
alsfile_Amazon_filepath <- unzip(alsfile_Amazon_zip,exdir = outdir)
alsfile_Savanna_filepath <- unzip(alsfile_Savanna_zip,exdir = outdir)
# Reading and plot ALS file (las file)
als_Amazon<-readLAS(alsfile_Amazon_filepath)
als_Savanna<-readLAS(alsfile_Savanna_filepath)
# Extracting plot center geolocations
xcenter_Amazon = mean(als_Amazon@bbox[1,])
ycenter_Amazon = mean(als_Amazon@bbox[2,])
xcenter_Savanna = mean(als_Savanna@bbox[1,])
ycenter_Savanna = mean(als_Savanna@bbox[2,])
# Simulating GEDI full waveform
wf_Amazon<-gediWFSimulator(input=alsfile_Amazon_filepath,
output=file.path(outdir,"gediWF_amazon_simulation.h5"),
coords = c(xcenter_Amazon, ycenter_Amazon))
wf_Savanna<-gediWFSimulator(input=alsfile_Savanna_filepath,
output=file.path(outdir,"gediWF_Savanna_simulation.h5"),
coords = c(xcenter_Savanna, ycenter_Savanna))
# Plot ALS and GEDI simulated full waveform
oldpar<-par()
par(mfrow=c(2,2), mar=c(4,4,0,0), oma=c(0,0,1,1),cex.axis = 1.2)
scatter3D(
als_Amazon@data$X,als_Amazon@data$Y,als_Amazon@data$Z,
pch = 16,colkey = FALSE, main="",
cex = 0.5,bty = "u",col.panel ="gray90",
phi = 30,alpha=1,theta=45,col.grid = "gray50",
xlab="UTM Easting (m)", ylab="UTM Northing (m)", zlab="Elevation (m)")
plot(wf_Amazon, relative=TRUE, polygon=TRUE, type="l", lwd=2, col="forestgreen",
xlab="", ylab="Elevation (m)", ylim=c(90,140))
grid()
scatter3D(
als_Savanna@data$X,als_Savanna@data$Y,als_Savanna@data$Z,
pch = 16,colkey = FALSE, main="",
cex = 0.5,bty = "u",col.panel ="gray90",
phi = 30,alpha=1,theta=45,col.grid = "gray50",
xlab="UTM Easting (m)", ylab="UTM Northing (m)", zlab="Elevation (m)")
plot(wf_Savanna, relative=TRUE, polygon=TRUE, type="l", lwd=2, col="green",
xlab="Waveform Amplitude (%)", ylab="Elevation (m)", ylim=c(815,835))
grid()
par(oldpar)
close(wf_Amazon)
close(wf_Savanna)
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