Estimating Leaf Area Index by Bayesian Linear Regression Using Terrestrial LiDAR, LAI-2200 Plant Canopy Analyzer, and Landsat TM Spectral Indices

Canadian Journal of Remote Sensing

Volumn 41, Issue 4, 2015, Pages 315-333

  Ilangakoon, Nayani T ^a,b   Gorsevski, Pece V ^a   Simic Milas, Anita ^a  

^a BOWLING GREEN STATE UNIVERSITY   (United States)

^b BOISE STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PLANTS (BOTANY); SCALES (WEIGHING INSTRUMENTS); SURVEYING INSTRUMENTS; UNCERTAINTY ANALYSIS;

BIO-PHYSICAL VARIABLES; NORMALIZED DIFFERENCE VEGETATION INDEX; ORTHOGRAPHIC PROJECTIONS; PARAMETER UNCERTAINTY; PERPENDICULAR VEGETATION INDEX; SPECTRAL VEGETATION INDICES; STEREOGRAPHIC PROJECTION; TERRESTRIAL LASER SCANNERS;

VEGETATION;

EID: 84950319308     PISSN: 07038992     EISSN: 17127971     Source Type: Journal    
DOI: 10.1080/07038992.2015.1102629     Document Type: Article

References (100)

1. G.P.Asner,, J.M.Scurlock,, and J.A.Hicke, 2003. “Global synthesis of leaf area index observations: Implications for ecological and remote sensing studies.” Global Ecology and Biogeography, Vol. 12(No. 3): pp. 191–205.
2. F.Baret,, and G.Guyot, 1991. “Potentials and limits of vegetation indices for LAI and APAR assessment.” Remote Sensing of Environment, Vol. 35(No. 2): pp. 161–173.
3. M.Béland,, J.L.Widlowski,, R.A.Fournier,, J.F.Côté,, and M.M.Verstraete, 2011. “Estimating leaf area distribution in savanna trees from terrestrial LiDAR measurements.” Agricultural and Forest Meteorology, Vol. 151(No. 9): pp. 1252–1266.
4. N.J.Bréda, 2003. “Ground‐based measurements of leaf area index: A review of methods, instruments and current controversies.” Journal of Experimental Botany, Vol. 54(No. 392): pp. 2403–2417.
5. L.Brown,, J.M.Chen,, S.G.Leblanc,, and J.Cihlar, 2000. “A shortwave infrared modification to the simple ratio for LAI retrieval in boreal forests: An image and model analysis.” Remote Sensing of Environment, Vol. 71(No. 1): pp. 16–25.
6. H.Bulcock,, and G.Jewitt, 2010. “Spatial mapping of leaf area index using hyperspectral remote sensing for hydrological applications with a particular focus on canopy interception.”Hydrology and Earth Systems Science, Vol. 14: pp. 383–392.
7. M.Cao,, and F.I.Woodward, 2002. “Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their responses to climate change.” Global Change Biology, Vol. 4(No. 2): pp. 185–198.
8. G.Chander,, and B.Markham, 2003. “Revised Landsat-5 TM radiometric calibration procedures and post calibration dynamic ranges.” IEEE Transactions on Geosciences and Remote Sensing, Vol. 41(No. 11): pp. 2674–2677.
9. L.Chasmer,, C.Hopkinson,, and P.Treitz, 2006. “Investigating laser pulse penetration through a conifer canopy by integrating airborne and terrestrial LiDAR.” Canadian Journal of Remote Sensing, Vol. 32(No. 2): pp. 116–125.
10. J.W.Chason,, D.D.Baldocchi,, and M.A.Huston, 1991. “A comparison of direct and indirect methods for estimating forest canopy leaf area.” Agricultural and Forest Meteorology, Vol. 57(No. 1): pp. 107–128.
11. J.M.Chen,, T.A.Black,, and R.S.Adams, 1991. “Evaluation of hemispherical photography for determining plant area index and geometry of a forest stand.” Agricultural and Forest Meteorology, Vol. 56(No. 1): pp. 129–143.
12. J.M.Chen, and T.A.Black, 1992. “Defining leaf area index for non-flat leaves.” Plant, Cell and Environment, Vol. 15: pp. 421–429.
13. J.M.Chen,, and J.Cihlar, 1995. “Quantifying the effect of canopy architecture on optical measurements of leaf area index using two gap size analysis methods.” Geoscience and Remote Sensing, Vol. 33(No. 3): pp. 777–787.
14. J.M.Chen,, and J.Cihlar, 1996. “Retrieving leaf area index of boreal conifer forests using Landsat TM images.” Remote Sensing of Environment, Vol. 55(No. 2): pp. 153–162.
15. J.M.Chen,, G.Pavlic,, L.Brown,, J.Cihlar,, S.G.Leblanc,, H.P.White,, and P.K.E.Pellikka, 2002. “Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements.”Remote Sensing of Environment, Vol. 80(No. 1): pp. 165–184.
16. J.M.Chen,, P.M.Rich,, S.T.Gower,, J.M.Norman,, and S.Plummer, 1997. “Leaf area index of boreal forests: Theory, techniques, and measurements.” Journal of Geophysical Research: Atmospheres (1984–2012), Vol. 102(No. D24): pp. 29429–29443.
17. J.M.Chen,, J.Liu,, S.G.Leblanc,, R.Lacaze,, and J.L.Roujean, 2003. “Multi-angular optical remote sensing for assessing vegetation structure and carbon absorption.” Remote Sensing of Environment, Vol. 84: pp. 516–525.
18. J.P.G.W.Clevers, 1989. The derivation of a simplified reflectance model for the estimation of leaf area index.” Remote Sensing of Environment, Vol. 25(No. 1): pp. 53–69.
19. J.Côté,, J.Widlowski,, R.A.Fournier,, and M.M.Verstraete, 2009. “The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial LiDAR.”Remote Sensing of Environment, Vol. 113(No. 5): pp. 1067–1081.
20. M.Crosetto,, and S.Tarantola, 2001. “Uncertainty and sensitivity analysis: Tools for GIS-based model implementation.” International Journal of Geographical Information Science, Vol. 15(No. 5): pp. 415–437.
21. M.Datcu,, K.Seidel,, and M.Walessa, 1998. “Spatial information retrieval from remote-sensing images. I. Information theoretical perspective.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 36(No. 5): pp. 1431–1445.
22. D.P.Davidson, 2002. Sensitivity of Ecosystem Net Primary Productivity Models to Remotely Sensed Leaf Area Index in a Montane Forest Environment. Doctoral dissertation, Lethbridge, AB, Canada: University of Lethbridge, Faculty of Arts and Science.
23. J.C.Dewey,, S.D.Roberts,, and I.Hartley, 2006. “A comparison of tools for remotely estimating leaf area index in loblolly pine plantations.” Proceedings of the 13th Biennial Southern Silvicultural Research Conference Gen. Tech. Rep. SRS, 92, 71–75.
24. J.C.Dewey,, S.D.Roberts,, and I.Hartley, 2006. “A comparison of tools for remotely estimating leaf area index in loblolly pine plantations.” Paper presented at the 13th Biennial Southern Silvicultural Research Conference.
25. J.Dong,, R.K.Kaufmann,, R.B.Myneni,, C.J.Tucker,, P.E.Kauppi,, J.Liski,, and M.K.Hughes, 2003. “Remote sensing estimates of boreal and temperate forest woody biomass: Carbon pools, sources, and sinks.” Remote Sensing of Environment, Vol. 84(No. 3): pp. 393–410.
26. E.Dufrêne,, and N.Bréda, 1995. “Estimation of deciduous forest leaf area index using direct and indirect methods.” Oecologia, Vol. 104(No. 2): pp. 156–162.
27. J.U.Eitel,, L.A.Vierling,, and D.S.Long, 2010. “Simultaneous measurements of plant structure and chlorophyll content in broadleaf saplings with a terrestrial laser scanner.” Remote Sensing of Environment, Vol. 114(No. 10): pp. 2229–2237.
28. K.S.Fassnacht,, S.T.Gower,, J.M.Norman,, and R.E.McMurtric, 1994. “A comparison of optical and direct methods for estimating foliage surface area index in forests.” Agricultural and Forest Meteorology, Vol. 71(No. 1): pp. 183–207.
29. G.M.Foody,, and P.M.Atkinson,, editors. 2002. Uncertainty in Remote Sensing and GIS. Chichester, UK: John Wiley & Sons.
30. G.W.Frazer,, C.D.Canham,, and K.P.Lertzman, 1999. Gap Light Analyzer (GLA), Version 2.0: Imaging Software to Extract Canopy Structure and Gap Light Transmission Indices from True-Colour Fisheye Photographs, Users Manual and Program Documentation. Burnaby, BC, Canada, and Millbrook, NY: Simon Fraser University and the Institute of Ecosystem Studies.
31. J.A.Gamon,, C.B.Field,, M.L.Goulden,, K.L.Griffin,, A.E.Hartley,, G.Joel,, and R.Valentini, 1995. “Relationships between NDVI, canopy structure, and photosynthesis in three Californian vegetation types.” Ecological Applications Vol. 5(No. 1), pp. 28–41.
32. M.A.Gilabert,, J.González-Piqueras,, F.J.Garcıa-Haro,, and J.Meliá, 2002. “A generalized soil-adjusted vegetation index.” Remote Sensing of Environment, Vol. 82(No. 2): pp. 303–310.
33. P.V.Gorsevski, 2013. “Using Bayesian inference to account for uncertainty in parameter estimates in modelled invasive flowering rush.” Remote Sensing Letters, Vol. 4(No. 3): pp. 279–287.
34. P.V.Gorsevski,, P.E.Gessler,, and P.Jankowski, 2003. “Integrating a fuzzy k-means classification and a Bayesian approach for spatial prediction of landslide hazard.” Journal of Geographical Systems, Vol. 5(No. 3): pp. 223–251.
35. Gorsevski, P.V., Gessler, P.E., and Jankowski P. 2010. “A fuzzy k-means classification and a Bayesian approach for spatial prediction of landslide hazard.” In Handbook of Applied Spatial Analysis, edited by M.M. Fischer and A. Getis, pp. 653–684. Heidelberg: Springer
36. D.P.Groeneveld, 1997. “Vertical point quadrat sampling and an extinction factor to calculate leaf area index.” Journal of Arid Environments, Vol. 36(No. 3): pp. 475–485.
37. A.Grêt-Regamey,, and D.Straub, 2006. “Spatially explicit avalanche risk assessment linking Bayesian networks to a GIS.” Natural Hazards and Earth System Science, Vol. 6(No. 6): pp. 911–926.
38. D.Haboudane,, J.R.Miller,, N.Tremblay,, P.J.Zarco-Tejada,, and L.Dextraze, 2002. “Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture.” Remote Sensing of Environment, Vol. 81(No. 2–3): pp. 416–426.
39. D.Haboudane,, J.R.Miller,, E.Pattey,, P.J.Zarco-Tejada,, and I.B.Strachan, 2004. “Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture.” Remote Sensing of Environment, Vol. 90(No. 3): pp. 337–352.
40. H.Hashimoto,, W.Wang,, C.Milesi,, M.A.White,, S.Ganguly,, M.Gamo,, and R.R.Nemani, 2012. “Exploring simple algorithms for estimating gross primary production in forested areas from satellite data.” Remote Sensing, Vol. 4(No. 1): pp. 303–326.
41. J.G.Henning,, and P.J.Radtke, 2006. “Ground-based laser imaging for assessing three dimensional forest canopy structure.” Photogrammetric Engineering and Remote Sensing, Vol. 72(No. 12): p. 1349–1358.
42. F.Hosoi,, and K.Omasa, 2006. “Voxel-based 3-D modeling of individual trees for estimating leaf area density using high-resolution portable scanning LiDAR.” IEEE Transactions on Geoscience and Remote Sensing, Vol. 44(No. 12): pp. 3610–3618.
43. F.Hosoi,, and K.Omasa, 2007. “Factors contributing to accuracy in the estimation of the woody canopy leaf area density profile using 3D portable LiDAR imaging.” Journal of Experimental Botany, Vol. 58(No. 12): pp. 3463–3473.
44. Houghton, R. A., Hall, F., and Goetz, S. J. 2009. “Importance of biomass in the global carbon cycle.” Journal of Geophysical Research: Biogeosciences, Vol. 114(No. G00E03). doi: 10.1029/2009JG000935
45. P.Huang,, and H.Pretzsch, 2010. “Using terrestrial laser scanner for estimating leaf areas of individual trees in a conifer forest.” Trees, Vol. 24(No. 4): pp. 609–619.
46. A.R.Huete, 1988. “A soil-adjusted vegetation index (SAVI).” Remote Sensing of Environment, Vol. 25(No. 3): pp. 295–309.
47. T.Iizumi,, M.Yokozawa,, and M.Nishimori, 2009. “Parameter estimation and uncertainty analysis of a large-scale crop model for paddy rice: Application of a Bayesian approach.” Agricultural and Forest Meteorology, Vol. 149(No. 2): pp. 333–348.
48. I.Jonckheere,, S.Fleck,, K.Nackaerts,, B.Muys,, P.Coppin,, M.Weiss,, and F.Baret, 2004. “Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography.” Agricultural and Forest Meteorology, Vol. 121(No. 1): pp. 19–35.
49. D.L.Jupp,, D.S.Culvenor,, J.L.Lovell,, G.J.Newnham,, A.H.Strahler,, and C.E.Woodcock, 2009. “Estimating forest LAI profiles and structural parameters using a ground-based laser called ‘Echidna®.’” Tree Physiology, Vol. 29(No. 2): pp. 171–181.
50. R.Kandwal,, C.Jeganathan,, V.Tolpekin,, and S.P.S.Kushwaha, 2009. “Discriminating the invasive species, ‘Lantana’ using vegetation indices.” Journal of the Indian Society of Remote Sensing, Vol. 37(No. 2): pp. 275–290.
51. D.A.Kwak,, W.K.Lee,, and H.K.Cho, 2007. “Estimation of LAI using LiDAR remote sensing in forest.” In Proceedings of ISPRS Workshop on Laser Scanning and SilviLaser, September 12–14, Espoo, Finland, pp. 248–252.
52. R.Lacaze,, J.M.Chen,, J.L.Roujean,, and S.G.Leblanc, 2002. Retrieval of vegetation clumping index using hot spot signatures measured by POLDER instrument.” Remote Sensing of Environment, Vol. 79: pp. 84–95.
53. G.Lasslop,, M.Reichstein,, D.Papale,, A.D.Richardson,, A.Arneth,, A.Barr, and G.Wohlfahrt, 2010. “Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: Critical issues and global evaluation.” Global Change Biology, Vol. 16(No. 1): pp. 187–208.
54. K.Lee,, W.B.Cohen,, R.E.Kennedy,, T.K.Maiersperger,, and S.T.Gower, 2004. “Hyperspectral versus multispectral data for estimating leaf area index in four different biomes.”Remote Sensing of Environment, Vol. 91(No. 3): pp. 508–520.
55. Leica Cyclone 3D point cloud processing software. 2013. Last modified June 10, 2013. http://www.leica-geosystems.us/en/Leica-Cyclone_6515.htm.
56. Leica Geosystems, 2005. Heerbrugg: Leica Geosystems AG. http://www.leica-geosystems.com (accessed May 2013).
57. P.Lewis, 2007. “3D canopy modelling as a tool in remote-sensing research.” Frontis, Vol. 22: 219–229.
58. LICOR Bioscience USA. 2011. LAI-2200 Plant Canopy Analyzer. Instruction Manual. Lincoln, NE: LICOR, Inc. Available at http://www.licor.com/ (accessed April 2013).
59. K.Lim,, P.Treitz,, M.Wulder,, B.St-Onge,, and M.Flood, 2003. “LiDAR remote sensing of forest structure.” Progress in Physical Geography, Vol. 27(No. 1): pp. 88–106.
60. J.Liu,, J.M.Chen,, J.Cihlar,, and W.Chen, 1999. “Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data.” Journal of Geophysical Research, Vol. 104(No. D22): pp. 27735–27754.
61. J.L.Lovell,, D.L.B.Jupp,, G.J.Newnham,, and D.S.Culvenor, 2011. “Measuring tree stem diameters using intensity profiles from ground-based scanning LiDAR from a fixed viewpoint.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 66(No. 1): pp. 46–55.
62. D.J.Lunn,, A.Thomas,, N.Best,, and D.Spiegelhalter, 2000. “WinBUGS—A Bayesian modelling framework: Concepts, structure, and extensibility.” Statistics and Computing, Vol. 10: pp. 325–337.
63. M.A.McCarthy, 2007. Bayesian Methods for Ecology. New York: Cambridge University Press.
64. M.Mencuccini,, and J.Grace, 1995. “Climate influences the leaf area/sapwood area ratio in scots pine.” Tree Physiology, Vol. 15(No. 1): pp. 1–10.
65. L.M.Moskal,, and G.Zheng, 2011. “Retrieving forest inventory variables with terrestrial laser scanning (TLS) in urban heterogeneous forest.” Remote Sensing, Vol. 4(No. 1): pp. 1–20.
66. H.H.Neumann,, G.Den Hartog,, and R.H.Shaw, 1989. “Leaf area measurements based on hemispheric photographs and leaf-litter collection in a deciduous forest during autumn leaf-fall.” Agricultural and Forest Meteorology, Vol. 45(No. 3): pp. 325–345.
67. A.Pacheco,, A.Bannari,, K.Staenz,, and H.Mcnairn, 2001. “LAI measurements in white beans and corn canopies with two optical instruments.” Paper presented at 8th International Symposium on Physical Measurements and Signatures in Remote Sensing, Aussois, France, January 8.
68. G.Patenaude,, R.A.Hill,, R.Milne,, D.L.Gaveau,, B.B.J.Briggs,, and T.P.Dawson, 2004. “Quantifying forest above ground carbon content using LiDAR remote sensing.” Remote Sensing of Environment, Vol. 93(No. 3): pp. 368–380.
69. G.Patenaude,, R.Milne,, M.Van Oijen,, C.S.Rowland,, and R.A.Hill, 2008. “Integrating remote sensing datasets into ecological modelling: A Bayesian approach.” International Journal of Remote Sensing, Vol. 29(No. 5): pp. 1295–1315.
70. C.Potter,, S.Klooster,, R.Crabtree,, S.Huang,, P.Gross,, and V.Genovese, 2011. “Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling.” Carbon Balance and Management, Vol. 6(No. 1): pp. 1–16.
71. J.Qi,, A.Chehbouni,, A.R.Huete,, Y.H.Kerr,, and S.Sorooshian, 1994. “A modified soil adjusted vegetation index.” Remote Sensing of Environment, Vol. 48(No. 2): pp. 119–126.
72. J.Qi,, Y.H.Kerr,, M.S.Moran,, M.Weltz,, A.R.Huete,, S.Sorooshian,, and R.Bryant, 2000. “Leaf area index estimates using remotely sensed data and BRDF models in a semiarid region.” Remote Sensing of Environment, Vol. 73(No. 1): pp. 18–30.
73. P.B.Reich,, D.P.Turner,, and P.Bolstad, 1999. “An approach to spatially distributed modeling of net primary production (NPP) at the landscape scale and its application in validation of EOS NPP products.” Remote Sensing of Environment, Vol. 70(No. 1): pp. 69–81.
74. A.D.Richardson,, D.B.Dail,, and D.Y.Hollinger, 2011. “Leaf area index uncertainty estimates for model–data fusion applications.” Agricultural and Forest Meteorology, Vol. 151(No. 9): pp. 1287–1292.
75. A.J.Richardson,, and C.L.Weigand, 1977. “Distinguishing vegetation from soil background information.” Photogrammetric Engineering and Remote Sensing, Vol. 43(No. 12), pp. 1541–1552.
76. J.W.Rouse,, R.H.Haas,, J.A.Shell,, D.W.Deering,, and J.C.Harlan, 1974. Monitoring the vernal advancement of retrogradation of natural vegetation, NASA/GSFC, Type III, Final Report, Greenbelt, MD. College Station, TX: Remote Sensing Center, Texas A&M University.
77. S.W.Running,, R.R.Nemani,, F.A.Heinsch,, M.Zhao,, M.Reeves,, and H.Hashimoto, 2004. “A continuous satellite-derived measure of global terrestrial primary production.” Bioscience, Vol. 54(No. 6): pp. 547–560.
78. T.A.Schetter, 2012. A Multiscale Spatial Analysis of Oak Openings Plant Diversity with Implications for Conservation and Management. Doctoral dissertation, Bowling Green State University.
79. A.Simic,, J.M.Chen,, J.Liu,, and F.Csillag, 2004. “Spatial scaling of net primary productivity using subpixel information.” Remote Sensing of Environment, Vol. 93, pp. 246–258.
80. Trimble, 2013. Yuma rugged tablet computer. Available at http://www.trimble.com/ (accessed March 2013).
81. D.P.Turner,, S.V.Ollinger,, and J.S.Kimball, 2004. “Integrating remote sensing and ecosystem process models for landscape-to regional-scale analysis of the carbon cycle.” BioScience, Vol. 54(No. 6): pp. 573–584.
82. D.P.Turner,, W.B.Cohen,, R.E.Kennedy,, K.S.Fassnacht,, and J.M.Briggs, 1999. “Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites.” Remote Sensing of Environment, Vol. 70(No. 1): pp. 52–68.
83. U.S. Department of Agriculture Forest Service. 2013. “Forests and carbon storage.” Last modified February 11, 2013. http://www.fs.fed.us/ccrc/topics/forests-carbon/
84. United Nations, 2013. Framework Convention on Climate Change. Last modified February 19, 2013. http://unfccc.int/2860.php.
85. D.Van der Zande,, W.Hoet,, I.Jonckheere,, J.van Aardt,, and P.Coppin, 2006. “Influence of measurement set-up of ground-based LiDAR for derivation of tree structure.” Agricultural and Forest Meteorology, Vol. 141(No. 2): pp. 147–160.
86. P.Van Gardingen,, G.Jackson,, S.Hernandez-Daumas,, G.Russell,, and L.Sharp, 1999. “Leaf area index estimates obtained for clumped canopies using hemispherical photography.”Agricultural and Forest Meteorology, Vol. 94(No. 3): pp. 243–257.
87. C.Walthall,, W.Dulaney,, M.Anderson,, J.Norman,, H.Fang,, and S.Liang, 2004. “A comparison of empirical and neural network approaches for estimating corn and soybean leaf area index from Landsat ETM+ imagery.” Remote Sensing of Environment, Vol. 92(No. 4): pp. 465–474.
88. S.Wang,, Y.Yang,, and A.P.Trishchenko, 2009. Assessment of canopy stomatal conductance models using flux measurements.” Ecological Modelling, Vol. 220: pp. 2115–2118.
89. M.Weiss,, F.Baret,, G.J.Smith,, I.Jonckheere,, and P.Coppin, 2004. “Review of methods for in situ leaf area index (LAI) determination Part II. Estimation of LAI, errors and sampling.” Agricultural and Forest Meteorology, Vol. 121: pp. 37–53.
90. J.Welles,, and J.Norman, 1991. “Instrument for indirect measurement of canopy architecture.” Agronomy Journal, Vol. 83(No. 5): pp. 818–825.
91. J.L.Widlowski,, M.Taberner,, B.Pinty,, V.Bruniquel‐Pinel,, M.Disney,, R.Fernandes,, J.-P.Gastellu-Etchegorry,, N.Gobron,, A.Kuusk,, T.Lavernge,, S.Leblanc,, P.E.Lewis,, E.Martin,, M.Motis,, P.R.J.North,, W.Qin,, M.Robustelli,, N.Rochdi,, R.Ruiloba,, C.Soler,, R.Thompson,, W.Verhoef,, M.M.Verstraete,, and D.Xie, 2007. “Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models.” Journal of Geophysical Research: Atmospheres (1984–2012), Vol. 112(No. D09111). doi: 10.1029/2006JD007821
92. B.A.Wintle,, M.A.McCarthy,, C.T.Volinsky,, and R.P.Kavanagh, 2003. “The use of Bayesian model averaging to better represent uncertainty in ecological models.” Conservation Biology, Vol. 17(No. 6): pp. 1579–1590.
93. Wu, J., Jones, B., Li, H., and Loucks, O.L. editors. 2006. Scaling and Uncertainty Analysis in Ecology. Dordrecht, the Netherlands: Springer.
94. T.Yao,, X.Yang,, F.Zhao,, Z.Wang,, Q.Zhang,, D.Jupp,, and A.Strahler, 2011. “Measuring forest structure and biomass in New England forest stands using echidna ground-based LiDAR.” Remote Sensing of Environment, Vol. 115(No. 11): pp. 2965–2974.
95. Yuma. 2013. Retrieved from http://www.laptopgpsworld.com/1561-gps-company-trimble-announces-its-1st-windows-based-portable-computer
96. S.Zaehle,, S.Sitch,, I.C.Prentice,, J.Liski,, W.Cramer,, M.Erhard,, and B.Smith, 2006. “The importance of age-related decline in forest NPP for modeling regional carbon balances.” Ecological Applications, Vol. 16(No. 4): pp. 1555–1574.
97. F.Zhao,, X.Yang,, M.A.Schull,, M.O.Román-Colón,, T.Yao,, Z.Wang,, and A.H.Strahler, 2011. “Measuring effective leaf area index, foliage profile, and stand height in New England forest stands using a full-waveform ground-based LiDAR.” Remote Sensing of Environment, Vol. 115(No. 11): pp. 2954–2964.
98. G.Zheng,, and L.M.Moskal, 2009. “Retrieving leaf area index (LAI) using remote sensing: Theories, methods and sensors.” Sensors, Vol. 9(No. 4): pp. 2719–2745.
99. G.Zheng,, and L.M.Moskal, 2012a. “Computational-geometry-based retrieval of effective leaf area index using terrestrial laser scanning.” Institute of Electrical and Electronic Engineers, Vol. 50(No. 10): pp. 3958–3969.
100. G.Zheng,, and L.M.Moskal, 2012b. “Spatial variability of terrestrial laser scanning based leaf area index.” International Journal of Applied Earth Observation and Geoinformation, Vol. 19: pp. 226–237.