Terrestrial vegetation and water balance—hydrological evaluation of ...
Terrestrial Laser Scanners for Vegetation Parameter Retrieval
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Transcript of 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
Department of Science, IT,
Innovation and the Arts
• 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.
Department of Science, IT,
Innovation and the Arts
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
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Study Site
D’Aguilar National Park (north west of Brisbane)
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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
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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
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• 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
Science, IT, Innovation and
the Arts
Data Analysis and Evaluation - Point Cloud Artefacts
Faro Focus
3D 120
Leica C10
Leica
HDS7000
Riegl
VZ1000
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• 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
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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
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• 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
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• 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
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Data Analysis and Evaluation - DEM ValidationDepartment of
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ALS Leica C10 Leica HDS7000 Riegl VZ1000Faro 3D 120
Example DEM surfaces
Data Analysis and Evaluation - Foliage Profile Comparison
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• 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
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First return only Weighted returns
Data Analysis and Evaluation - Foliage Profile Comparison Riegl VZ1000
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• 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
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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.
Department of Science, IT,
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• 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
Department of Science, IT,
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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.
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AcknowledgementsCR Kennedy and Faro for providing the TLS
demonstrations.
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Innovation and the Arts
Contact Details