1. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 1 The CSIRO Canopy Lidar Initiative, its ECHIDNA® and an EVI David LB Jupp 1, Darius Culvenor 2, Jenny Lovell 1 & Glenn Newnham 2 1 CSIRO Marine & Atmospheric Research (CMAR); 2 CSIRO Forestry and Forest Products (ENSIS) David LB Jupp 1, Darius Culvenor 2, Jenny Lovell 1 & Glenn Newnham 2 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 2006

2. 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

3. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 3 The simplest of illustrations (1) Same Cover/DAI higher for Clumped Constant size Lognormal sizeClumped DAI is mean area of disks per unit area Cover is mean area covered by disk per unit area

4. 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%

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

6. 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

7. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 7 Ground Based Lidar (ECHIDNA®)

8. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 8 EVI (The ECHIDNA® Validation Instrument)

9. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 9 Principles of Lidar Ranging

10. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 10 Hard & Soft Returns in EVI Data Tree TrunkFoliage

11. 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

12. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 12 ECHIDNA® Data Projections Hemispherical Plate Carre (simple cylindrical) Horizontal & Radial Slices

13. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 13 Hemisphere Data – Generalising Hemispherical Photography EVI Data – Mean over range Hemispherical Photograph

14. 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

15. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 15 EVI can provide Pgap as a function of Range

16. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 16 Gap to range - animation

17. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 17 Pgap Model for EVI data

18. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 18 Mean Waveforms

19. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 19 Model for Lidar Returns

20. 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  Height   Zenith 

21. 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  Zenith   Radius 

22. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 22 Field Data Stem Plot & EVI Stem Plot  Radius  Field Data EVI

23. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 23 ECHIDNA® Products – height, LAI & Stem location, size distribution and density

24. 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

25. 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

26. 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

27. CSIRO Marine & Atmospheric Research (CMAR) & ENSIS 27 A “Real” (not ®) Echidna – in the forest

28. 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