terrestrial laser scanners for vegetation parameter retrieval

Terrestrial Laser Scanners for Vegetation Parameter Retrieval

Department of Science, IT,

Innovation and the Arts

Presented by Jasmine Muir

Remote Sensing CentreEcosciences Precinct, Dutton ParkDepartment of Science, IT, Innovation and the Arts

Contributors

Glenn Newnham1, John Armston2,4, Jasmine Muir2, Nicholas Goodwin2,Darius Culvenor1, Kim Calders3, Kasper Johansen4,5, Dan Tindall2, Pyare Püschel6, Mattias Nyström7

Affiliations:1 CSIRO Land and Water; Private Bag 10, Clayton South, VIC 3169, Australia2 Remote Sensing Centre; Department of Science, Information Technology,Innovation and the Arts; Ecosciences Precinct, 41, Boggo Road, Dutton Park QLD, Australia, 41023 Laboratory of Geo-Information Science and Remote Sensing; Wageningen University; Droevendaalsesteeg, Wageningen 6708,

PB, The Netherlands4 Joint Remote Sensing Research Program; School of Geography, Planning and Environmental Management; University of

Queensland; Brisbane, Australia, 40725 Terrestrial Ecosystem Research Network (TERN) Auscover, School of Geography, Planning and Environmental Management;

University of Queensland;Brisbane,Australia, 40726 University of Trier, Trier, Germany7Swedish University of Agricultural Sciences, Sweden

Presentation Outline

• Purpose

• Background

• Study Site and Sampling Design

• Data Pre-Processing

• Data Analysis and Evaluation

• Discussion and Future Research

• Conclusions



• The objective of this work was to examine key differences in the data recorded by current commercial Terrestrial Laser Scanners (TLS) when operated in a forest environment.

• Parameters tested:– Scan resolution

– Scan quality

• Outcomes from the work have been used to inform the purchase decision of a TLS by RSC and TERN for vegetation structure monitoring.



Purpose

Background – Why Use TLS?

• Reduced field time for staff

• Increased data collection ability

• Provide a reference data set i.e. airborne lidar

• Different view (looking under the canopy)

• Measure different parameters

Scanner Attributes

Instrument Riegl VZ1000 Leica C10 Leica HDS7000 Faro Focus 3D 120

Supplier CR Kennedy CR Kennedy CR Kennedy LSS

Ranging method Time-of-flight Time-of-flight Phase Phase

Returns multiple single single single

Wavelength 1550nm 532nm 1500nm 905nm

Max Zenith Range 100 270 320 320

Laser Class 1 3R 1 3R

Range 1.5-1400m 600@20% 0.1-300m 134@18% 0.3-187m 0.6-120m

Samples/sec 122000 50000 1016000 976000

Scan Configuration 30-130 zenith Hemispherical Hemispherical Hemispherical

Colour external integrated external integrated

Weight 10kg 13kg 10kg 5kg

Temp Range 0-40C 0-40C 0-45C 5-40C



Study Site

D’Aguilar National Park (north west of Brisbane)



Sampling Design – TLS PlacementDepartment of

Science, IT, Innovation and

the Arts

Stem Measurements• Stem diameter (at 1.3m and 0.3m)• Crown opacity• Crown dimensions (length and

width)• Tree Height (top and first branch)• Total station position (x,y,z) relative

to scanner• Hemispherical photographs• Licor LAI2200

Study SiteLeica C10

Faro Focus 3D 120



Data Pre-Processing - Proprietary Software and Data Export

• Each scanner manufacturer has a proprietary data processing software system.

• Software not sufficient for all of our processing• Data exported to ptx format (an ASCII format) except

for Riegl which was exported to LAS format

• To associate multiple returns from the Riegl with a single pulse azimuth and zenith, low-level access to the raw binary files was necessary using Riegl C++ RiVLib library



• Phase based scanners: – return random ranges in canopy gaps due to sky and direct

solar radiation.– are subject to range averaging when the beam intercepts

multiple objects.

• Sky points need to be removed so gaps can be identified.• The removal of points that indicate multiple hits would

overly inflate gap probability estimates at the stand level, however to determine parameters for individual trees these points must be removed.

Data Pre-Processing - Filtering Phase Based DataDepartment of


the Arts

Data Analysis and Evaluation - Point Cloud Artefacts

Faro Focus

3D 120

Leica C10

Leica

HDS7000

Riegl

VZ1000



• Phase scanners provide inbuilt hardware and software filtering options – appeared non-ideal

• Used a range based kernel filter to allow consistent batch processing and remove points in canopy gaps.

Data Pre-Processing - Filtering Phase Based DataDepartment of


the Arts

HDS7000

Non-Filtered Default Filtering Range Kernel Filtering

• DEM generation from the scan allows vegetation structure to be analysed in terms of height relative to the ground surface, rather than relative to the origin of the sensor coordinate system.

• A DEM from each scan was derived at a scale of 1m.• Each DEM generated was validated using an

equivalent DEM generated using airborne laser scanning (ALS).

Data Pre-Processing - DEM GenerationDepartment of


the Arts

• Range Summaries

• Gap probability (Pgap)

• Leaf area index (LAI) or plant area index (PAI) as a cumulative profile

• foliage profile, sometimes referred to as the foliage area volume density (FAVD)

Data Pre-Processing - Vertical Foliage Profiles



• Range distribution for points recorded by each scanner• Similar for all resolutions for all scanners except for Faro• General pattern is the same between scanners although

some difference with the Riegl (no data >30deg. zenith)

Data Analysis and Evaluation - Range Summaries



Data Analysis and Evaluation - DEM ValidationDepartment of


the Arts

ALS Leica C10 Leica HDS7000 Riegl VZ1000Faro 3D 120

Example DEM surfaces

Data Analysis and Evaluation - Foliage Profile Comparison



• Correcting for terrain height is necessary for analysis of vegetation structure in areas of varied topography. Assume planar surface in flat areas.

• Maximum height decrease at both sites• Bimodal canopy response to unimodal canopy response

Data Analysis and Evaluation - Foliage Profile Comparison



First return only Weighted returns

Data Analysis and Evaluation - Foliage Profile Comparison Riegl VZ1000



• Findings include:– Pulse density has a negligible impact.– Quality of phase-shift data filtering directly impacts the variance in

metrics derived from gap fraction.– signal-to-noise ratio that can be achieved is highly dependent on

levels of ambient light.

• Occlusion by near-range terrain and vegetation has a greater impact on DEM error than sensor properties or scan settings.

• Phase-shift scanners: – needed filtering applied to accurately detect canopy gaps– range averaging when there are multiple targets in beam– higher scan integration time decreased signal-to-noise ratio– Faro size and weight make field operation easy

• Time of flight scanners:– relatively clean data (i.e. no range averaging)– Riegl multiple returns/waveform increases the information available

Data Analysis and Evaluation - DiscussionDepartment of


the Arts

• Development of data filtering and ground return classification algorithms for phase-based data.

• Improved estimation of gap fraction to account for terrain, wood area and volume fractions, clumping and to assess sensitivity to different leaf area projection functions.

• Linking airborne and ground-based estimates of structural measurements for calibration and validation of larger area mapping from lidar.


Innovation and the ArtsData Analysis and Evaluation - Future

• Compare scanner results to actual field measurements of DBH, height, biomass, LAI, canopy cover, foliage profile. Absolute field truth???

• Stand attributes vs individual trees

• Average from each scan rather than registration of multiple scans


Innovation and the ArtsData Analysis and Evaluation - Future

Conclusions

• 4 scanners tested at Brisbane Forest Park:– FARO Focus 3D 120– Leica HDS7000– Leica C10 and – Riegl VZ1000

• Time-of-flight instruments are currently providing the best characterisation of vegetation structure, particularly foliage measurements in the upper parts of the canopy, where multiple beam interceptions are not accommodated well by the phase-shift scanners.



AcknowledgementsCR Kennedy and Faro for providing the TLS

demonstrations.



Contact Details

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