77
Kobayashi H, Iwabuchi H (2008) A coupled 1-D atmosphere and 3-D canopy radiative transfer
model for canopy reflectance, light environment, and photosynthesis simulation in a heterogeneous landscape. Remote Sens Environ 112:173–185
Kokaly RF, Asner GP, Ollinger SV, Martin ME, Wessman CA (2009) Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies. Remote Sens
Environ 113:S78–S91
Kokaly RF, Clark RN (1999) Spectroscopic determination of leaf biochemistry using band-depth
analysis of absorption features and stepwise multiple linear regression. Remote Sens Environ
67:267–287
Kokaly RF, Skidmore AK (2015) Plant phenolics and absorption features in vegetation reflectance
spectra near 1.66μm. Int J Appl Earth Obs Geoinf 43:55–83
Krinov EL (1953) Spectral reflectance properties of natural formations. National Research Council
of Canada (Ottawa) Technical Translations TT-439
Kuusk A (2018) 3.03 - Canopy radiative transfer modeling. In: Liang S (ed). Comprehensive Remote
Sensing. Oxford: Elsevier, 9–22, https://doi.org/10.1016/B978-0-12-409548-9.10534-2
Kuusk A, Nilson T (2000) A directional multispectral forest reflectance model. Remote Sens
Environ 72:244–252
Lavorel S, Garnier E (2002) Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. Funct Ecol 16:545–556
LeBauer D, Kooper R, Mulrooney P, Rohde S, Wang D, Long SP, Dietze MC (2018) BETYdb: a
yield, trait, and ecosystem service database applied to second-generation bioenergy feedstock
production. GCB Bioenergy 10(1):61–71
Li D, Wang X, Zheng H, Zhou K, Yao X, Tian Y, Zhu Y, Cao W, Cheng T (2018) Estimation of
area- and mass-based leaf nitrogen contents of wheat and rice crops from water-removed
spectra using continuous wavelet analysis. Plant Methods 14:76
Li L, Cheng YB, Ustin S, Hu XT, Riaño D (2008) Retrieval of vegetation equivalent water thickness from reflectance using genetic algorithm (GA)-partial least squares (PLS) regression. Adv
Space Res 41:1755–1763
Mand P, Hallik L, Penuelas J, Nilson T, Duce P, Emmett BA, Beier C, Estiarte M, Garadnai J,
Kalapos T, Schmidt IK, Kovacs-Lang E, Prieto P, Tietema A, Westerveld JW, Kull O (2010)
Responses of the reflectance indices PRI and NDVI to experimental warming and drought in
European shrublands along a north-south climatic gradient. Remote Sens Environ 114:626–636
Martin ME, Aber JD (1997) High spectral resolution remote sensing of forest canopy lignin, nitrogen, and ecosystem processes. Ecol Appl 7:431–443
Martin ME, Plourde LC, Ollinger SV, Smith ML, McNeil BE (2008) A generalizable method for
remote sensing of canopy nitrogen across a wide range of forest ecosystems. Remote Sens
Environ 112:3511–3519
Matson P, Johnson L, Billow C, Miller J, Pu RL (1994) Seasonal patterns and remote spectral
estimation of canopy chemistry across the Oregon transect. Ecol Appl 4:280–298
McNeil BE, Read JM, Sullivan TJ, McDonnell TC, Fernandez IJ, Driscoll CT (2008) The spatial
pattern of nitrogen cycling in the Adirondack Park, New York. Ecol Appl 18:438–452
McNicholas HJ (1931) The visible and ultraviolet absorption spectra of carotin and xanthophyll
and the changes accompanying oxidation. Bureau of Standards Journal of Research 7(1):171.
Research Paper 337 (RP337)
Middleton EM, Ungar SG, Mandl DJ, Ong L, Frye SW, Campbell PE, Landis DR, Young JP,
Pollack NH (2013) The Earth observing one (EO-1) satellite mission: over a decade in space.
IEEE J Sel Top Appl Earth Obs Remote Sens 6:243–256
Miller CE, Green RO, Thompson DR, Thorpe AK, Eastwood M, Mccubbin IB, Olson-Duvall
W, Bernas M, Sarture CM, Nolte S, Rios LM, Hernandez MA, Bue BD, Lundeen SR (2019)
ABoVE: Hyperspectral Imagery from AVIRIS-NG, Alaskan and Canadian Arctic, 2017-2018.
ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1569
Mirik M, Norland JE, Crabtree RL, Biondini ME (2005) Hyperspectral one-meter-resolution
remote sensing in yellowstone National Park, Wyoming: I. Forage nutritional values. Rangel
Ecol Manag 58:452–458
3 Scaling Functional Traits from Leaves to Canopies
Kobayashi H, Iwabuchi H (2008) A coupled 1-D atmosphere and 3-D canopy radiative transfer
model for canopy reflectance, light environment, and photosynthesis simulation in a heterogeneous landscape. Remote Sens Environ 112:173–185
Kokaly RF, Asner GP, Ollinger SV, Martin ME, Wessman CA (2009) Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies. Remote Sens
Environ 113:S78–S91
Kokaly RF, Clark RN (1999) Spectroscopic determination of leaf biochemistry using band-depth
analysis of absorption features and stepwise multiple linear regression. Remote Sens Environ
67:267–287
Kokaly RF, Skidmore AK (2015) Plant phenolics and absorption features in vegetation reflectance
spectra near 1.66μm. Int J Appl Earth Obs Geoinf 43:55–83
Krinov EL (1953) Spectral reflectance properties of natural formations. National Research Council
of Canada (Ottawa) Technical Translations TT-439
Kuusk A (2018) 3.03 - Canopy radiative transfer modeling. In: Liang S (ed). Comprehensive Remote
Sensing. Oxford: Elsevier, 9–22, https://doi.org/10.1016/B978-0-12-409548-9.10534-2
Kuusk A, Nilson T (2000) A directional multispectral forest reflectance model. Remote Sens
Environ 72:244–252
Lavorel S, Garnier E (2002) Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail. Funct Ecol 16:545–556
LeBauer D, Kooper R, Mulrooney P, Rohde S, Wang D, Long SP, Dietze MC (2018) BETYdb: a
yield, trait, and ecosystem service database applied to second-generation bioenergy feedstock
production. GCB Bioenergy 10(1):61–71
Li D, Wang X, Zheng H, Zhou K, Yao X, Tian Y, Zhu Y, Cao W, Cheng T (2018) Estimation of
area- and mass-based leaf nitrogen contents of wheat and rice crops from water-removed
spectra using continuous wavelet analysis. Plant Methods 14:76
Li L, Cheng YB, Ustin S, Hu XT, Riaño D (2008) Retrieval of vegetation equivalent water thickness from reflectance using genetic algorithm (GA)-partial least squares (PLS) regression. Adv
Space Res 41:1755–1763
Mand P, Hallik L, Penuelas J, Nilson T, Duce P, Emmett BA, Beier C, Estiarte M, Garadnai J,
Kalapos T, Schmidt IK, Kovacs-Lang E, Prieto P, Tietema A, Westerveld JW, Kull O (2010)
Responses of the reflectance indices PRI and NDVI to experimental warming and drought in
European shrublands along a north-south climatic gradient. Remote Sens Environ 114:626–636
Martin ME, Aber JD (1997) High spectral resolution remote sensing of forest canopy lignin, nitrogen, and ecosystem processes. Ecol Appl 7:431–443
Martin ME, Plourde LC, Ollinger SV, Smith ML, McNeil BE (2008) A generalizable method for
remote sensing of canopy nitrogen across a wide range of forest ecosystems. Remote Sens
Environ 112:3511–3519
Matson P, Johnson L, Billow C, Miller J, Pu RL (1994) Seasonal patterns and remote spectral
estimation of canopy chemistry across the Oregon transect. Ecol Appl 4:280–298
McNeil BE, Read JM, Sullivan TJ, McDonnell TC, Fernandez IJ, Driscoll CT (2008) The spatial
pattern of nitrogen cycling in the Adirondack Park, New York. Ecol Appl 18:438–452
McNicholas HJ (1931) The visible and ultraviolet absorption spectra of carotin and xanthophyll
and the changes accompanying oxidation. Bureau of Standards Journal of Research 7(1):171.
Research Paper 337 (RP337)
Middleton EM, Ungar SG, Mandl DJ, Ong L, Frye SW, Campbell PE, Landis DR, Young JP,
Pollack NH (2013) The Earth observing one (EO-1) satellite mission: over a decade in space.
IEEE J Sel Top Appl Earth Obs Remote Sens 6:243–256
Miller CE, Green RO, Thompson DR, Thorpe AK, Eastwood M, Mccubbin IB, Olson-Duvall
W, Bernas M, Sarture CM, Nolte S, Rios LM, Hernandez MA, Bue BD, Lundeen SR (2019)
ABoVE: Hyperspectral Imagery from AVIRIS-NG, Alaskan and Canadian Arctic, 2017-2018.
ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1569
Mirik M, Norland JE, Crabtree RL, Biondini ME (2005) Hyperspectral one-meter-resolution
remote sensing in yellowstone National Park, Wyoming: I. Forage nutritional values. Rangel
Ecol Manag 58:452–458
3 Scaling Functional Traits from Leaves to Canopies