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Background

Frontiers in Fuels Science: Species-Specific Crown Profiles Models from Terrestrial Laser Scanning. 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)

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Background

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Presentation Transcript

  1. Frontiers in Fuels Science: Species-Specific Crown Profiles Models from Terrestrial Laser Scanning

  2. 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

  3. 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

  4. Introduction: Sampling Vicinity Map • Connection to Destructive Samples • Collect TLS data of sampled trees • Collect independent samples concurrently representing: • same species • site conditions • TLS Sampling Objective • n > 200 Trees sampled Trees & TLS sampled

  5. Introduction: TLS Instrument OptechIlris 36D HD Terrestrial Lidar System • 10 KHz sampling • Point density 1cm or less • Local characterization

  6. Introduction: TLS Sampling • Current Thinking: • Literature suggests that estimating biomass from TLS requires: Zone of Occlusion • Scanning from multiple angles • High resolution • Offsetting potential occlusion of data within tree • 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 Zone of Interception 15m Minimum Distance

  7. Introduction: TLS Sampling • 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 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) Origin

  8. 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.

  9. Methods: TLS-Based Bole Measurements • Three Estimates of Bole Diameter Up The Tree: Three samples of distance from bole centroid Fitted line from selected bole points Modeled from the initial bole diameter at the bottom of the tree

  10. Methods: Distance and Tree Cleaning

  11. Methods: Building a Library of Crown Shapes Height (m) Distance (m)

  12. Analysis • Species used in preliminary work • Crown Characterization • Crown Shapes (profiles and lengths) • Biomass Distribution • Bole characterization • Integrating it all • What’s next?

  13. Analysis • Data sample for preliminary analysis • 6 Douglas firs (Pseudosugamensiesii) • 3 grand firs (Abiesgrandis) • 1 ponderosa pine (Pinus ponderosa) • 1 western larch (Larixoccidenatlis) http://www.idahoforests.org

  14. Analysis: Crown Profiles • 90th crown width percentile chosen to define outer hull • Points at each height interval

  15. Analysis: Crown Profiles • Rescaled both axes as 0-1 • Did this for 6 Douglas firs and 3 grand firs

  16. Analysis: Crown Profiles • Combined all samples per species into one “uber-tree” each

  17. Analysis: Crown Profiles • Model Fitting • curve smoothing • scale of variability • exclusion of bole/incorporation of crown base height

  18. Analysis: Crown Profiles Douglas Fir (n=6) Grand Fir (n=3) Ponderosa Pine (n=1) Western Larch (n=1)

  19. Analysis: Crown Base Height Using some impartial metric to consistently define lower bound of crown length

  20. Analysis: Crown Base Height

  21. Analysis: Crown Base Height / Crown Profiles

  22. Analysis: Crown Biomass Distribution • Hull / void • Survivability analysis • Hull delineation • Within-hull biomass distribution

  23. Analysis: Boles • Many different radius measures generated curve fitted constant dist1 dist2 dist3 average dist

  24. Analysis: Boles • Potential use in linking TLS data to allometry for biomass prediction • Problems to overcome

  25. 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

  26. 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

  27. 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.

  28. Acknowledgements: • Joint Fire Sciences Program • Inland Northwest Growth and Yield Cooperative • Affleck lab • Active Remote Sensing Lab, National Center for Landscape Fire Analysis

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