UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications...
Transcript of UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications...
![Page 2: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/2.jpg)
Introduction
• Introduction to LiDAR RS for vegetation• Review instruments and observational concepts• Discuss applications arising for measuring and
monitoring vegetation– primarily forests
![Page 3: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/3.jpg)
Why LiDAR?
• Main reason:– (relatively) direct measurement of tree/canopy height– Tree height strongly correlated to other properties
• Woody biomass• Age etc.
• BRDF and other radiometric RS– Need to infer properties from signal
![Page 4: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/4.jpg)
Alternative technologies
• Stereo Photogrammetry– Tree height in sparse canopies
• Need to extract ground height
• InSAR– Scattering height not directly canopy height
• Density, wavelength, polarisation
– Need to subtract ground height
![Page 5: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/5.jpg)
![Page 6: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/6.jpg)
![Page 7: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/7.jpg)
Basis of LiDAR measurement
• t = 2 d / c
• h = d1- d2= (c/2) (t1- t2)
• c = 299.79 x106 m/s– i.e. 4.35 ns flight time per m
d1
d2
h
![Page 8: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/8.jpg)
Wavelength
• Typically use NIR1064 nm
• Green leavesscatter strongly
• Atmospherictransmission high
![Page 9: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/9.jpg)
Platform and scanning
• Requires precise knowledge of platform locationand orientation– GPS– INS
• Typically mirror scanning– On aircraft
![Page 10: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/10.jpg)
Types of LiDAR system
• Discrete return• ‘Waveform’
Time (distance)
![Page 11: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/11.jpg)
Discrete return LiDAR
• Airborne• Small footprint
![Page 12: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/12.jpg)
Small footprint
• beam high chance of penetratingholes in a vegetation canopy– to provide ground samples
• height measurement more easilyassociated with a single ‘object’– rather than blurred over some area– i.e. greater chance of hitting a
‘hard’ target.
• e.g. 0.1 mrad from 1000 mgiving a footprint of around10 cm at nadir
![Page 13: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/13.jpg)
Small footprint
• Chance may miss tree tops– Horizontal sampling important
• May double count
![Page 14: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/14.jpg)
Discrete return LiDAR
• Most modern systems:– First and last return
– need to distinguish crown/ground points
![Page 15: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/15.jpg)
Crown/ground points
• Can use e.g. local minima to determine ground
• And/or intensity of return
![Page 16: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/16.jpg)
Complicating effects
• High slope cancomplicate localminima filtering
• As can anyunderstorey
![Page 17: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/17.jpg)
Waveform LiDAR
• Sample returned energy– Into equal time (distance) bins
![Page 18: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/18.jpg)
Use larger footprint (10s of m)
• Backscattered energy low– Increased signal (integral over area)
• Enable measurement of whole tree (canopy)– and ground
• Trade-off with slope effects
![Page 19: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/19.jpg)
Ground signal more spread for slope (or roughness)
More likely to become mixed with canopy signal for higher slopes
![Page 20: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/20.jpg)
GLAS on IceSat: 70 m footprint
• ground slope of 10o
– ground signal to be spread over 70tan10o
– 12.34m• complicates ability to retrieve canopy information over anything
but very flat ground– 5o for GLAS?
• LVIS: 25 m footprint– Apparently little real slope effect (4.4 m spread for 10o)– Same order effect as other uncertainties
• Position• multiple scattering• Gaussian energy distribution across footprint
![Page 21: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/21.jpg)
Example systems: Discrete Return
• Cambridge University– Optech ALTM 3033 LiDAR
• Piper Navajo Chieftain aircraft
• 33,000 obs per s• first and last returns and intensity• operating altitude of 1000 metres
– RMS ht. accuracy of < +/- 15cms
• made available to NERC ARSF
![Page 22: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/22.jpg)
Other UK operators
• Environment Agency• Infoterra
– using similar systems
• Airborne Discrete return LiDAR very much operationalsystem
• Most information extraction simple height maps– But multitude of practical uses for these
![Page 23: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/23.jpg)
Waveform LiDAR
• SLICER– NASA
instrument1990s+
Scanning Lidar Imager of Canopies by Echo Recovery
![Page 24: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/24.jpg)
SLICER
• swath of five 10-m diameter footprints• waveform 11 cm vertical sampling (0.742 ns)• and can be flown at relatively high altitudes
– e.g. 5000m AGL in Means et al, 1999• Horizontal positioning accuracy is around 5-10m• Larger receiver telescope than illuminated beam
flightpath
telescopeFOV
swat
h wi
dth
![Page 25: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/25.jpg)
Multiple scattering
• Large footprint, particularly larger receiver givesrise to multiple scattering influence on signal
• Visible as below-ground signal
![Page 26: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/26.jpg)
p1
p2
p3
![Page 27: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/27.jpg)
First order scattering
With multiple scattering
Measurement
SLICER forest measurementsand modelling
Note magnitude of groundreturns
![Page 28: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/28.jpg)
Very ‘rich’ 3D dataset
![Page 29: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/29.jpg)
Vegetation Canopy LiDAR (VCL)
Spaceborne concept
Also CARBON-3D concept(with multi-angular spectroradiometer)
![Page 30: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/30.jpg)
LVIS (Laser Vegetation Imaging Sensor) Airborne simulator for VCL 25 m footprints with 20 m along- and across-track sampling.
![Page 31: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/31.jpg)
LVIS data product
![Page 32: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/32.jpg)
GLAS (Geoscience LaserAltimeter System) LiDAR,launched in 2003.
70 m footprint, so not designedfor vegetation applications,although active area of research inrecent years.
![Page 33: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/33.jpg)
Very rich source of information
![Page 34: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/34.jpg)
ECHIDNA ground-based waveform LiDAR
![Page 35: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/35.jpg)
![Page 36: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/36.jpg)
Information Extraction
![Page 37: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/37.jpg)
Direct Measurements
• canopy height, sub-canopy topography and verticaldistribution of intercepted surfaces
• direct or near-direct information from LiDAR• either of the LiDAR systems considered here
– (discrete return and waveform)
![Page 38: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/38.jpg)
Caveats
• discrete return systems– forest density is not too high
• for both: complicating factors– e.g. high slopes, very rough ground or sub-canopies– slope only important to small footprint systems for local
spatial operations• e.g. local minima filtering
![Page 39: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/39.jpg)
Caveats
• ‘hit’ may not come very top of a tree– tree shoulders in discrete return down-bias estimates of canopy height– Impact varies with tree shape and density
• e.g. more problematic for conical trees• apply some calibration to LiDAR-measured tree heights
– particularly from discrete return systems• other methods e.g. use upper 10% or so of heights
![Page 40: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/40.jpg)
Caveats
• waveform systems have larger footprints– can be difficult to defining tree height at such scales– One technique use the top five tree heights of a plot
• (a common measurement in forestry)• since this is what a large footprint lidar would see.
• if locational accuracy order of 5-10m– Can be difficult to locate trees precisely for ground comparisons
![Page 41: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/41.jpg)
Canopy vertical distribution
• Waveform LiDAR:– Vertical distribution of intercepted elements– Need to convert to vertical distribution of LAI/biomass
• If assume first-order scattering only– with a spherical angular distribution– with no clumping (as is usually the case)
– straightforward to calculate required attenuation terms– and transform the signal into an estimate of the vertical vegetation profile
• More complex to account for other effects– Need RT model– And possibly other sources (e.g. multi-angular hyperspectral)
![Page 42: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/42.jpg)
Empirical relationships
• Canopy height strongly related to– Basal area– Stem diameter– Biomass– Timber volume etc.
– Through allometric relations used in forestry– Many empirical models linking these.
![Page 43: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/43.jpg)
Canopy Cover
• Various attempts at this– E.g. waveform:
• soil peak relative tovegetation signal
![Page 44: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/44.jpg)
Tree number density
• Tree counting– From discrete return systems– Local maxima & minima
• Ground and crown
– High resolution classification of e.g. NDVI
![Page 45: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/45.jpg)
Popescu et al., 2003 http://filebox.vt.edu/users/wynne/(%234482)Popescu%20et%20al%202003%20crown%20diameter%20CJRS.pdf
![Page 46: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/46.jpg)
![Page 47: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/47.jpg)
![Page 48: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/48.jpg)
Radiative Transfer modelling and Inversion
• Various attempts at RT LiDAR modelling– RT (Sun and Ranson)– Ray tracing (Govaerts, Lewis)– GORT (Ni-Meister)
• Interesting recent attempt at RT model inversion– Koetz et al. 2006
![Page 49: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/49.jpg)
RT Inversion
![Page 50: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/50.jpg)
RT Inversion
![Page 51: UoL MSc Remote Sensingplewis/lidarforvegetation/lidarRS.pdf · LiDAR for vegetation applications UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk](https://reader030.fdocuments.net/reader030/viewer/2022020302/5a7596417f8b9a0d558c8161/html5/thumbnails/51.jpg)
Conclusion
• Two types of LiDAR system– Discrete return, waveform
• Discrete return (small footprint)– Standard monitoring instrument from aircraft platforms– Range of useful parameters can be derived
• Waveform (large footprint)– More experimental– But very rich source of data on 3D structure