csiro marine & atmospheric research (cmar) & ensis 1 the csiro canopy lidar initiative, its...
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CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 1
The CSIRO Canopy Lidar Initiative, its ECHIDNA® and an EVI
David LB Jupp1, Darius Culvenor2, Jenny Lovell1 & Glenn Newnham2 1 CSIRO Marine & Atmospheric Research (CMAR); 2 CSIRO Forestry and Forest Products (ENSIS)
David LB Jupp1, Darius Culvenor2, Jenny Lovell1 & Glenn Newnham2 1 CSIRO Marine & Atmospheric Research (CMAR); 2 CSIRO Forestry and Forest Products (ENSIS)
Presented at the IWMMM-4 Meeting in Sydney, Australia, March 20-24 2006Presented at the IWMMM-4 Meeting in Sydney, Australia, March 20-24 2006
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 2
Canopy Structure
Forest structure is complex – very complex
Canopy, trunks and stems are rarely measured as a total
Every method for measuring LAI gets a different answer
The best methods are laborious and time consuming – ie expensive
Foresters only see the trunks, environmental people see the leaves
The most significant aspects of canopy structure remain unmeasurable at all but a few sites
Forest structure is complex – very complex
Canopy, trunks and stems are rarely measured as a total
Every method for measuring LAI gets a different answer
The best methods are laborious and time consuming – ie expensive
Foresters only see the trunks, environmental people see the leaves
The most significant aspects of canopy structure remain unmeasurable at all but a few sites
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 3
The simplest of illustrations (1)Same Cover/DAI higher for Clumped
Constant size Lognormal size Clumped
DAI is mean area of disks per unit area
Cover is mean area covered by disk per unit area
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 4
The simplest of illustrations (2)Same DAI but Cover changes for Clumped
CF=5.3% CF=28.2% CF=71.5%
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 5
How should we measure the things that are the same and the things that are different?
The histograms are the same if the cover is the same.
In one case the DAI was the same in the other the Cover so what is different?
The spatial statistics change: length distributions, spatial density, the way histograms change with scale, variograms and local variance change
The difference is in the morphology therefore to measure the differences (and the similarities) you need an instrument that measures morphology
The histograms are the same if the cover is the same.
In one case the DAI was the same in the other the Cover so what is different?
The spatial statistics change: length distributions, spatial density, the way histograms change with scale, variograms and local variance change
The difference is in the morphology therefore to measure the differences (and the similarities) you need an instrument that measures morphology
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 6
Echidna® – A Ground Based Lidar
CSIRO EOC canopy Lidar Initiative (CLI) arose to promote innovative R&D, applications and commercial opportunities for airborne and ground based Lidar
ECHIDNA® is a ground based lidar technology identified by CSIRO as a potential tool for forest and vegetation structural measurement
The ECHIDNA® and its research prototype – the ECHIDNA® Validation Instrument (or “EVI”) have key differences from scanning rangefinders
Digitise the full ‘waveform’
Have variable beam divergence
Use full hemispherical scanning
Have linear response and calibration
CSIRO EOC canopy Lidar Initiative (CLI) arose to promote innovative R&D, applications and commercial opportunities for airborne and ground based Lidar
ECHIDNA® is a ground based lidar technology identified by CSIRO as a potential tool for forest and vegetation structural measurement
The ECHIDNA® and its research prototype – the ECHIDNA® Validation Instrument (or “EVI”) have key differences from scanning rangefinders
Digitise the full ‘waveform’
Have variable beam divergence
Use full hemispherical scanning
Have linear response and calibration
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 7
Ground Based Lidar (ECHIDNA®)
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 8
EVI (The ECHIDNA® Validation Instrument)
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 9
Principles of Lidar Ranging
0 2
2( ) t
p
RI t t t
c R
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 10
Hard & Soft Returns in EVI Data
Tree Trunk Foliage
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 11
Styles of product and processing
There are three basic ways that the EVI data are being analysed Stand based information from foliage profiles and stem returns (eg cover and LAI
with height, layering, stand & bole height variation, mean DBH, density and basal area);
Stand based counting information from stems and trees (eg basal area, stem density, size and stand and bole heights);
Tree based estimation of stem and foliage factors (eg leaf to stem ratios, crown size, form factor (taper), multi-stems and defect);
Each one can be made easier by projecting and re-formatting the data in different ways
There are three basic ways that the EVI data are being analysed Stand based information from foliage profiles and stem returns (eg cover and LAI
with height, layering, stand & bole height variation, mean DBH, density and basal area);
Stand based counting information from stems and trees (eg basal area, stem density, size and stand and bole heights);
Tree based estimation of stem and foliage factors (eg leaf to stem ratios, crown size, form factor (taper), multi-stems and defect);
Each one can be made easier by projecting and re-formatting the data in different ways
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 12
ECHIDNA® Data Projections
Hemispherical
Plate Carre (simple cylindrical)
Horizontal & Radial Slices
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 13
Hemisphere Data – Generalising Hemispherical Photography
EVI Data – Mean over range Hemispherical Photograph
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 14
However, there is a lot more information about the trees in EVI than in Hemispherical photography
EVI data provides strong separation between foliage profile (LAI), green height and stem profile (BA) – they are now analysed separately
Larundal Biomass Site - Holbrook
Crowns
Trunks
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 15
EVI can provide Pgap as a function of Range
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 16
Gap to range - animation
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 17
Pgap Model for EVI data
( , ) ( , ) / cos ( , )( , ) LG F r A rgapP r e
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 18
Mean Waveforms
2
( )( , ) * ( ) ( , )shot Hit
K rI r CI p P r
r
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 19
Model for Lidar Returns
( , ) ( cos ) / cos ( , )
2
( ) ( ) ( , )( , ) * ( , ) ( ) ( ) LG F r A r
shot L L t t
K r F z A rI r CI p g G p e
r z r
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 20
The data can also be “sliced” by radial distance providing tree silhouettes
Range Moments 10, 12 & 14 (Near Range)
Range Slice 15-17 m away from and above EVI for branching, defect and shape of stems
H
eight
Zenith
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 21
The data can be “sliced” by height providing stem (trunk) plots and horizontal canopy slices
Range Moments 18, 20 & 22 (Far Range comparison)
Height Slices 0.25, 1.75 & 3.75 m above EVI provide stem information
Z
enith
Radius
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 22
Field Data Stem Plot & EVI Stem Plot
R
adius Field Data
EVI
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 23
ECHIDNA® Products – height, LAI & Stem location, size distribution and density
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 24
Current applications of ECHIDNA®
Primary Information Foliage profile & LAI Stocking, Basal Area & DBH distribution (C) Stem maps and identification (C) Tree silhouettes (C) Bole height & branching (C)
In Progress Stem form factor, taper and sweep (by size class) (C) Separating branches and foliage Allometry from ground to airborne data
The potentials in forestry & ecology are almost unlimited
Primary Information Foliage profile & LAI Stocking, Basal Area & DBH distribution (C) Stem maps and identification (C) Tree silhouettes (C) Bole height & branching (C)
In Progress Stem form factor, taper and sweep (by size class) (C) Separating branches and foliage Allometry from ground to airborne data
The potentials in forestry & ecology are almost unlimited
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 25
Mapping the Canopy Structure – the “Star”
The eye normally see the “trees” rather than the “gap”
Watch the light areas and not the black!
The “Star” is the radial extent of the Laser illumination and displays the structure of the “gap” from the EVI position and where the laser “illuminates” the forest and where it does not
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 26
The radial average “Star” as an ECHIDNA®
The structure of the Star has the same information as the Trees.
The first and second order properties give us cover and BRDF by range
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 27
A “Real” (not ®) Echidna – in the forest
CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 28
Current & Future work program
Commercialisation of a focused EVI/Echidna® for forest measurement
Test sites and a field mission in the US (spring of 2007?) where airborne canopy Lidar has been used (LVIS) for airborne/ground based allometry
Development of new methods for LAI, clumping, gap size distributions, BDRF functions, visibility and multi-component characterisation of forests as ecological systems
Applications to ecology and environment (using the “Star” and its structure) are major scientific goals
Commercialisation of a focused EVI/Echidna® for forest measurement
Test sites and a field mission in the US (spring of 2007?) where airborne canopy Lidar has been used (LVIS) for airborne/ground based allometry
Development of new methods for LAI, clumping, gap size distributions, BDRF functions, visibility and multi-component characterisation of forests as ecological systems
Applications to ecology and environment (using the “Star” and its structure) are major scientific goals