Background
description
Transcript of Background
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Frontiers in Fuels Science:
Species-Specific Crown Profiles Models from Terrestrial Laser Scanning
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Background
Key Concepts: Document accuracy and validity of existing crown biomass equations
(Affleck)
Develop new crown biomass/fuel equations for inland northwest tree species (Affleck)
Parameterize crown fuel density profiles over individual stems per species with TLS
• Stem dimensions• Crown characteristics (e.g. shape and density)
Where We’ve Come From: Branch Scale Biomass Using TLS
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Background: Working Hypotheses (TLS)
Boles• Incremental bole diameters used to generate basal area• Diameters could be used predict biomass from revised allometries
Crown profiles differ between species• A large body of previous work on crown shapes• Laser gives precise measurements and characterize crown• High replication using laser• Tests using limited sample sizes suggest between species differences
are more pronounced than those within species
Biomass is distributed unequally throughout a crown:• Both vertically and horizontally• Distribution differs between species
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Introduction: Sampling
Vicinity Map
Trees sampled Trees & TLS sampled
Connection to Destructive Samples
• Collect TLS data of sampled trees
• Collect independent samples concurrently representing:− same species− site conditions
TLS Sampling Objective• n > 200
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Introduction: TLS Instrument
Optech Ilris 36D HD Terrestrial Lidar System• 10 KHz sampling• Point density 1cm or less• Local characterization
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Introduction: TLS Sampling
Project Approach: This project seeks to optimize TLS
collection by:
• Limit scanning time by only sampling a hemisphere
• Control errors of omission through sampling volume
15mMinimum Distance
Zone of Interception
Zone of Occlusion
Current Thinking: Literature suggests that estimating
biomass from TLS requires:• Scanning from multiple angles• High resolution• Offsetting potential occlusion of
data within tree
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Introduction: TLS Sampling
Focal Plane (~4.0mm density)
Types of Occlusion: Penetration of energy through the
canopy or objects • Angle independent/dependent
Shadowing of canopy elements • Depends canopy density• Angularity (branches shadowing
objects above)
Data Resolution a Function of Range: The instrument is parameterized to
collect data at a set resolution at a determined range (focal plane)
Characterize hull of tree
Data decreases in density as it gains range
Origin
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Methods: TLS Collection and Processing
Data Process Flow Data Collection
• Largest time commitment (e.g. travel, set up, Etc.)• ~15 minutes per scan• Dependent on site conditions (e.g. adjacent tree
density)
Alignment of Scans (Polyworks)• Potentially time consuming
Process Using Lab Developed Applications• Designed to begin optimizing tree processing for
efficiency and repeatability• Single processing flow for applying alignment,
calculating bole dimensions, and normalized canopy distance from
bole.
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Methods: TLS-Based Bole Measurements
Three Estimates of Bole Diameter Up The Tree:1. Three samples of distance
from bole centroid2. Fitted line from selected
bole points3. Modeled from the initial
bole diameter at the bottom of the tree
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Methods: Distance and Tree Cleaning
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Methods: Building a Library of Crown ShapesH
eigh
t (m
)
Distance (m)
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Analysis
• Species used in preliminary work• Crown Characterization
• Crown Shapes (profiles and lengths)• Biomass Distribution
• Bole characterization• Integrating it all• What’s next?
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Analysis
• Data sample for preliminary analysis• 6 Douglas firs (Pseudosuga mensiesii)• 3 grand firs (Abies grandis)• 1 ponderosa pine (Pinus ponderosa)• 1 western larch (Larix occidenatlis)
http://www.idahoforests.org
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Analysis: Crown Profiles
• 90th crown width percentile chosen to define outer hull
• Points at each height interval
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Analysis: Crown Profiles
• Rescaled both axes as 0-1
• Did this for 6 Douglas firs and 3 grand firs
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Analysis: Crown Profiles
• Combined all samples per species into one “uber-tree” each
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Analysis: Crown Profiles
Model Fitting• curve smoothing• scale of variability• exclusion of
bole/incorporation of crown base height
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Analysis: Crown Profiles
Douglas Fir (n=6)Grand Fir (n=3)Ponderosa Pine (n=1)Western Larch (n=1)
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Analysis: Crown Base Height
Using some impartial metric to consistently define lower bound of crown length
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Analysis: Crown Base Height
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Analysis: Crown Base Height / Crown Profiles
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Analysis: Crown Biomass Distribution
• Hull / void
• Survivability analysis
• Hull delineation
• Within-hull biomass distribution
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Analysis: Boles
• Many different radius measures generated
curvefitted
constant dist1 dist2 dist3 averagedist
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Analysis: Boles
• Potential use in linking TLS data to allometry for biomass prediction
• Problems to overcome
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Analysis: Integrating It All
Per Species• Apply crown base metric• Generate the “uber-tree”• Fit crown profile curve• Determine hull-void
demarcation• Determine biomass
allocation pattern
For New Trees• Need species, DBH,
height, crown length• Use DBH to calculate
biomass• Use crown profile
function to build outer hull shape
• Allocate biomass within defined hull
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Analysis: Where To Next…
Things to think about:• Occlusions (of bole, inner vegetation)• Best metric for CBH delineation• Appropriate scale of variation for crown profile
curve• Defining hull/void demarcation • Distributing biomass within that hull
Next (this summer through Spring 2013)• More trees, more scanning, more data processing• Linkages to Affleck lab measures• Exploration of applications beyond fire
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The Laser Team:
Eric Rowell, Ph.D. Plot scale surface fuels characterization; integration of airborne and terrestrial scanning, fuel consumption.
Tara Umphries, M.S. Quantifying fuel dimensions in a grassland.
Jena Ferrarese, M.S. Measuring conifer crown dimensions and the distribution of biomass within them.
Theodore Adams, M.S. Defining/distributing fuel elements in diffuse shrubs of sagebrush and chamise.
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Acknowledgements:
Joint Fire Sciences Program Inland Northwest Growth and Yield Cooperative Affleck lab Active Remote Sensing Lab, National Center for Landscape Fire Analysis