-
Yuri Knyazikhin,
Philip Lewis,
Mathias I Disney,
Matti Mõttus,
Miina Rautiainen,
Pauline Stenberg,
Robert K Kaufmann,
Alexander Marshak,
Mitchell A Schull,
Pedro Latorre Carmona,
Vern Vanderbilt,
Anthony B Davis,
Frédéric Baret,
Stéphane Jacquemoud,
Alexei Lyapustin,
Yan Yang,
Ranga B Myneni
[show abstract]
[hide abstract]
ABSTRACT: Various physical, chemical, and physiological processes, including canopy structure, impact surface reflectance. Remote sensing aims to derive ecosystem properties and their func-tional relationships, given these impacts. Ollinger et al. (1) do not distinguish between the forward and inverse problems in radiative transfer and, hence, misrepresent our results (2). The authors also suggest our conclusions are based on a subset of data from ref. 3, which is not the case. Remote sensing instruments do not mea-sure canopy properties, only photons that enter the canopy, interact with foliage, woody material, and ground, and escape toward the sensor. Fundamental laws of light interaction with matter describe this process and provide causal mechanisms to explain observations. We report an explicit relationship between radiation measured by an optical sensor, canopy structural properties, and leaf op-tics (Eq. S6.1 in ref. 2) and demonstrate its validity over a wide range of forests (SI Text 7 and figure 6 in ref. 2). The relationship was derived from well-established principles of light interaction with leaves and radiative-transfer theory. Our conclusions are based on this result, not on "[u]sing a subset of data from ref. ([3])." We used data from ref. 3 to: (i) reproduce Ollinger et al.'s result (figure 3 in ref. 2); (ii) analyze their methodology; (iii) demonstrate flaws in their interpretation (figure 2 in ref. 2); and (iv) formulate the in-verse problem of inferring leaf-scattering properties from satellite data. We demonstrate that the link between near-infrared reflectance (NIR) and foliar nitrogen (%N) is both indirect and a function of structure (across the entire shortwave domain). In situ %N, too, is a function of structure because foliar nitrogen in ref. 3 was "determined as the mean of mass-based foliar %N over all species in each plot (weighted by the relative abundance of each)." In both cases we found canopy structure dominated variations in NIR reflectance with %N, result-ing in spurious correlation (2). We therefore disagree with Ollinger et al. (1, 3) that the observed NIR vs. %N relationship alone adequately justifies its use in remote sensing: reflectance data must be corrected for can-opy structure effects to extract information about %N and other chemical constituents. Furthermore, we identified the directional area scattering factor (DASF) as a means to achieve this correction. DASF is a purely structural term, directly obtainable from can-opy reflectance spectra, and does not "rely on an assumption that a useful link between nitrogen and reflectance requires a direct, biochemical mechanism" (1). Our report does not per se rule out indirect connections between nitrogen availability and structure, but it does allow the direct relationship between leaf nitrogen and remote sensing signals to be elucidated without needing such an assumption. Although biological mechanisms certainly shape complex linkages between ecosystem components, canopy radiative response is the only source of information about ecosystem properties from remote sensing, and follows physical laws governing radiation transport. Our analysis explains the observed behavior entirely through application of these laws, but Ollinger et al. (1) appeal to more complex and as yet unspecified ecological and evo-lutionary mechanisms to explain their obser-vations: Ockham's razor (4) surely applies. Physically based approaches must under-lie remote sensing analysis of ecosystem properties and functional relationships be-tween their components (5).
Proceedings of the National Academy of Sciences 05/2013; · 9.68 Impact Factor
-
Yuri Knyazikhin,
Philip Lewis,
Mathias I Disney,
Matti Mõttus,
Miina Rautiainen,
Pauline Stenberg,
Robert K Kaufmann,
Alexander Marshak,
Mitchell A Schull,
Pedro Latorre Carmona,
Vern Vanderbilt,
Anthony B Davis,
Frédéric Baret,
Stéphane Jacquemoud,
Alexei Lyapustin,
Yan Yang,
Ranga B Myneni
[show abstract]
[hide abstract]
ABSTRACT: Various physical, chemical, and physiological processes, including canopy structure, impact surface reflectance. Remote sensing aims to derive ecosystem properties and their func-tional relationships, given these impacts. Ollinger et al. (1) do not distinguish between the forward and inverse problems in radiative transfer and, hence, misrepresent our results (2). The authors also suggest our conclusions are based on a subset of data from ref. 3, which is not the case. Remote sensing instruments do not mea-sure canopy properties, only photons that enter the canopy, interact with foliage, woody material, and ground, and escape toward the sensor. Fundamental laws of light interaction with matter describe this process and provide causal mechanisms to explain observations. We report an explicit relationship between radiation measured by an optical sensor, canopy structural properties, and leaf op-tics (Eq. S6.1 in ref. 2) and demonstrate its validity over a wide range of forests (SI Text 7 and figure 6 in ref. 2). The relationship was derived from well-established principles of light interaction with leaves and radiative-transfer theory. Our conclusions are based on this result, not on "[u]sing a subset of data from ref. ([3])." We used data from ref. 3 to: (i) reproduce Ollinger et al.'s result (figure 3 in ref. 2); (ii) analyze their methodology; (iii) demonstrate flaws in their interpretation (figure 2 in ref. 2); and (iv) formulate the in-verse problem of inferring leaf-scattering properties from satellite data. We demonstrate that the link between near-infrared reflectance (NIR) and foliar nitrogen (%N) is both indirect and a function of structure (across the entire shortwave domain). In situ %N, too, is a function of structure because foliar nitrogen in ref. 3 was "determined as the mean of mass-based foliar %N over all species in each plot (weighted by the relative abundance of each)." In both cases we found canopy structure dominated variations in NIR reflectance with %N, result-ing in spurious correlation (2). We therefore disagree with Ollinger et al. (1, 3) that the observed NIR vs. %N relationship alone adequately justifies its use in remote sensing: reflectance data must be corrected for can-opy structure effects to extract information about %N and other chemical constituents. Furthermore, we identified the directional area scattering factor (DASF) as a means to achieve this correction. DASF is a purely structural term, directly obtainable from can-opy reflectance spectra, and does not "rely on an assumption that a useful link between nitrogen and reflectance requires a direct, biochemical mechanism" (1). Our report does not per se rule out indirect connections between nitrogen availability and structure, but it does allow the direct relationship between leaf nitrogen and remote sensing signals to be elucidated without needing such an assumption. Although biological mechanisms certainly shape complex linkages between ecosystem components, canopy radiative response is the only source of information about ecosystem properties from remote sensing, and follows physical laws governing radiation transport. Our analysis explains the observed behavior entirely through application of these laws, but Ollinger et al. (1) appeal to more complex and as yet unspecified ecological and evo-lutionary mechanisms to explain their obser-vations: Ockham's razor (4) surely applies. Physically based approaches must under-lie remote sensing analysis of ecosystem properties and functional relationships be-tween their components (5).
Proceedings of the National Academy of Sciences 05/2013; · 9.68 Impact Factor
-
Yuri Knyazikhin,
Philip Lewis,
Mathias I Disney,
Matti Mõttus,
Miina Rautiainen,
Pauline Stenberg,
Robert K Kaufmann,
Alexander Marshak,
Mitchell A Schull,
Pedro Latorre Carmona,
Vern Vanderbilt,
Anthony B Davis,
Frédéric Baret,
Stéphane Jacquemoud,
Alexei Lyapustin,
Yan Yang,
Ranga B Myneni
[show abstract]
[hide abstract]
ABSTRACT: Various physical, chemical, and physiological processes, including canopy structure, impact surface reflectance. Remote sensing aims to derive ecosystem properties and their func-tional relationships, given these impacts. Ollinger et al. (1) do not distinguish between the forward and inverse problems in radiative transfer and, hence, misrepresent our results (2). The authors also suggest our conclusions are based on a subset of data from ref. 3, which is not the case. Remote sensing instruments do not mea-sure canopy properties, only photons that enter the canopy, interact with foliage, woody material, and ground, and escape toward the sensor. Fundamental laws of light interaction with matter describe this process and provide causal mechanisms to explain observations. We report an explicit relationship between radiation measured by an optical sensor, canopy structural properties, and leaf op-tics (Eq. S6.1 in ref. 2) and demonstrate its validity over a wide range of forests (SI Text 7 and figure 6 in ref. 2). The relationship was derived from well-established principles of light interaction with leaves and radiative-transfer theory. Our conclusions are based on this result, not on "[u]sing a subset of data from ref. ([3])." We used data from ref. 3 to: (i) reproduce Ollinger et al.'s result (figure 3 in ref. 2); (ii) analyze their methodology; (iii) demonstrate flaws in their interpretation (figure 2 in ref. 2); and (iv) formulate the in-verse problem of inferring leaf-scattering properties from satellite data. We demonstrate that the link between near-infrared reflectance (NIR) and foliar nitrogen (%N) is both indirect and a function of structure (across the entire shortwave domain). In situ %N, too, is a function of structure because foliar nitrogen in ref. 3 was "determined as the mean of mass-based foliar %N over all species in each plot (weighted by the relative abundance of each)." In both cases we found canopy structure dominated variations in NIR reflectance with %N, result-ing in spurious correlation (2). We therefore disagree with Ollinger et al. (1, 3) that the observed NIR vs. %N relationship alone adequately justifies its use in remote sensing: reflectance data must be corrected for can-opy structure effects to extract information about %N and other chemical constituents. Furthermore, we identified the directional area scattering factor (DASF) as a means to achieve this correction. DASF is a purely structural term, directly obtainable from can-opy reflectance spectra, and does not "rely on an assumption that a useful link between nitrogen and reflectance requires a direct, biochemical mechanism" (1). Our report does not per se rule out indirect connections between nitrogen availability and structure, but it does allow the direct relationship between leaf nitrogen and remote sensing signals to be elucidated without needing such an assumption. Although biological mechanisms certainly shape complex linkages between ecosystem components, canopy radiative response is the only source of information about ecosystem properties from remote sensing, and follows physical laws governing radiation transport. Our analysis explains the observed behavior entirely through application of these laws, but Ollinger et al. (1) appeal to more complex and as yet unspecified ecological and evo-lutionary mechanisms to explain their obser-vations: Ockham's razor (4) surely applies. Physically based approaches must under-lie remote sensing analysis of ecosystem properties and functional relationships be-tween their components (5).
Proceedings of the National Academy of Sciences 05/2013; · 9.68 Impact Factor
-
Yuri Knyazikhin,
Philip Lewis,
Mathias Disney,
Matti Mottus,
Miina Rautiainen,
Pauline Stenberg,
Robert Kauffman,
Alexander Marshak,
Mitchell Schull,
Pedro Latorre Carmona,
Vern Vanderbilt,
Anthony B Davis,
Frederic Baret,
Stephane Jacquemoud,
Alexei Lyapustin,
Yan Yang,
Ranga Myneni
Proceedings of the National Academy of Sciences 05/2013; · 9.68 Impact Factor
-
Yuri Knyazikhin,
Philip Lewis,
Mathias Disney,
Matti Mottus,
Miina Rautiainen,
Pauline Stenberg,
Robert Kauffman,
Alexander Marshak,
Mitchell Schull,
Pedro Latorre Carmona,
Vern Vanderbilt,
Anthony B Davis,
Frederic Baret,
Stephane Jacquemoud,
Alexei Lyapustin,
Yan Yang,
Ranga Myneni
Proceedings of the National Academy of Sciences 05/2013; · 9.68 Impact Factor
-
Yuri Knyazikhin,
Philip Lewis,
Mathias I Disney,
Pauline Stenberg,
Matti Mõttus,
Miina Rautiainen,
Robert K Kaufmann,
Alexander Marshak,
Mitchell A Schull,
Pedro Latorre Carmona,
Vern Vanderbilt,
Anthony B Davis,
Frédéric Baret,
Stéphane Jacquemoud,
Alexei Lyapustin,
Yan Yang,
Ranga B Myneni
Proceedings of the National Academy of Sciences 03/2013; 110(12):E1075. · 9.68 Impact Factor
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Yuri Knyazikhin,
Mitchell A Schull,
Pauline Stenberg,
Matti Mõttus,
Miina Rautiainen,
Yan Yang,
Alexander Marshak,
Pedro Latorre Carmona,
Robert K Kaufmann,
Philip Lewis,
Mathias I Disney,
Vern Vanderbilt,
Anthony B Davis,
Frédéric Baret,
Stéphane Jacquemoud,
Alexei Lyapustin,
Ranga B Myneni
[show abstract]
[hide abstract]
ABSTRACT: A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact-it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423-855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710-790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.
Proceedings of the National Academy of Sciences 12/2012; · 9.68 Impact Factor
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David J. Diner,
Thomas P. Ackerman,
Amy Braverman,
Carol J. Bruegge,
Mark J. Chopping,
Eugene E. Clothiaux,
Roger Davies,
Larry Di Girolamo,
Ralph A. Kahn, Yuri Knyazikhin, [......],
Jan-Peter Muller,
Anne W. Nolin,
Bernard Pinty,
Michel M. Verstraete,
Dong L. Wu,
Michael J. Garay,
Olga V. Kalashnikova,
Anthony B. Davis,
Edgar S. Davis,
Russell A. Chipman
IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2010, July 25-30, 2010, Honolulu, Hawaii, USA, Proceedings; 01/2010
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Ranga B Myneni,
Wenze Yang,
Ramakrishna R Nemani,
Alfredo R Huete,
Robert E Dickinson, Yuri Knyazikhin,
Kamel Didan,
Rong Fu,
Robinson I Negrón Juárez,
Sasan S Saatchi, [......],
Eric F Vermote,
David P Roy,
Robert E Wolfe,
Mark A Friedl,
Steven W Running,
Petr Votava,
Nazmi El-Saleous,
Sadashiva Devadiga,
Yin Su,
Vincent V Salomonson
[show abstract]
[hide abstract]
ABSTRACT: Despite early speculation to the contrary, all tropical forests studied to date display seasonal variations in the presence of new leaves, flowers, and fruits. Past studies were focused on the timing of phenological events and their cues but not on the accompanying changes in leaf area that regulate vegetation-atmosphere exchanges of energy, momentum, and mass. Here we report, from analysis of 5 years of recent satellite data, seasonal swings in green leaf area of approximately 25% in a majority of the Amazon rainforests. This seasonal cycle is timed to the seasonality of solar radiation in a manner that is suggestive of anticipatory and opportunistic patterns of net leaf flushing during the early to mid part of the light-rich dry season and net leaf abscission during the cloudy wet season. These seasonal swings in leaf area may be critical to initiation of the transition from dry to wet season, seasonal carbon balance between photosynthetic gains and respiratory losses, and litterfall nutrient cycling in moist tropical forests.
Proceedings of the National Academy of Sciences 04/2007; 104(12):4820-3. · 9.68 Impact Factor
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IEEE International Geoscience & Remote Sensing Symposium, IGARSS 2007, July 23-28, 2007, Barcelona, Spain, Proceedings; 01/2007
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IEEE T. Geoscience and Remote Sensing. 01/2006; 44:1829-1842.
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Wenze Yang,
Bin Tan,
Dong Huang,
Miina Rautiainen,
Nikolay V. Shabanov,
Yujie Wang,
Jeffrey L. Privette,
Karl Fred Huemmrich,
Rasmus Fensholt,
Inge Sandholt,
Marie Weiss,
Douglas E. Ahl,
Stith T. Gower,
Ramakrishna R. Nemani, Yuri Knyazikhin,
Ranga B. Myneni
IEEE T. Geoscience and Remote Sensing. 01/2006; 44:1885-1898.
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IEEE T. Geoscience and Remote Sensing. 01/2006; 44:1866-1871.
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David J. Diner,
Bobby H. Braswell,
Roger Davies,
Nadine Gobron,
Jiannan Hu,
Yufang Jin,
Ralph A. Kahn, Yuri Knyazikhin,
Norman Loeb,
Jan-Peter Muller,
Anne W. Nolin,
Bernard Pinty,
Crystal B. Schaaf,
Gabriela Seiz,
Julienne Stroeve
[show abstract]
[hide abstract]
ABSTRACT: Passive optical multiangle observations make possible the retrieval of scene structural characteristics that cannot be obtained with, or require fewer underlying assumptions than, single-angle sensors. Retrievable quantities include aerosol amount over a wide variety of surfaces (including bright targets); aerosol microphysical properties such as particle shape; geometrically-derived cloud-top heights and 3-D cloud morphologies; distinctions between polar clouds and ice; and textural measures of sea ice, ice sheets, and vegetation. At the same time, multiangle data are necessary for accurate retrievals of radiative quantities such as surface and top-of-atmosphere albedos, whose magnitudes are governed by structural characteristics of the reflecting media and which involve angular integration over intrinsically anisotropic intensity fields. Measurements of directional radiation streams also provide independent checks on model assumptions conventionally used in satellite retrievals, such as the application of 1-D radiative transfer theory, and provide data required to constrain more sophisticated, 3-D approaches. In this paper, the value of multiangle remote sensing in establishing physical correspondence and self-consistency between scene structural and radiative characteristics is demonstrated using simultaneous observations from instruments aboard NASA's Terra satellite (MISR, CERES, ASTER, and MODIS). Illustrations pertaining to the remote sensing of clouds, aerosols, ice, and vegetation properties are presented.
Remote Sensing of Environment 01/2005; 97:495-518. · 4.57 Impact Factor
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Nikolay V. Shabanov,
Dong Huang,
Wenze Yang,
Bin Tan, Yuri Knyazikhin,
Ranga B. Myneni,
Douglas E. Ahl,
Stith T. Gower,
Alfredo R. Huete,
Luiz Eduardo Oliveira E. Cruz de Aragão,
Yosio Edemir Shimabukuro
IEEE T. Geoscience and Remote Sensing. 01/2005; 43:1855-1865.
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Bin Tan,
Jiannan Hu,
Ping Zhang,
Dong Huang,
Nikolay Shabanov,
Marie Weiss, Yuri Knyazikhin,
Ranga B Myneni,
Citation : Tan,
J Hu,
P Zhang,
D Huang,
N Shabanov,
M Weiss,
Y Knyazikhin,
R B Myneni
[show abstract]
[hide abstract]
ABSTRACT: 1] This paper presents results of validating the Collection 4 Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) product using LAI data collected in a 3 Â 3 km agricultural (grasses and cereal crops) area near Avignon, France, and 30 m resolution Enhanced Thematic Mapper (ETM+) image. Estimates of the accuracy, precision, and uncertainty with which the ETM+ data convey information about LAI underlie the derivation of a 30 m resolution reference LAI map by accounting for both field measurement and satellite observation errors. The 30 m reference LAI was then extrapolated from sampling points to a 58 km 2 area without loss in the quality and was degraded to a 1 km resolution LAI map. The latter was taken as a reference to assess the quality of the MODIS LAI product. Comparison of the reference and corresponding MODIS retrievals suggests that Collection 4 MODIS LAI is accurate to within an accuracy of 0.3 with a precision and uncertainty of 0.23 and 0.38, respectively. It was found that the Collection 3 MODIS land cover product, input to the Collection 4 operational LAI algorithm, misclassified the 58 km 2 area as broadleaf crops. The use of correct biome type in the operational processing improves the accuracy in LAI by a factor of 2 with an almost unchanged precision and uncertainty. Our results also indicate that the retrieval of LAI from satellite data is an ill-posed problem; that is, small variations in input due to observation errors result in a very low precision of the desired parameter. Any retrieval technique based on a simple model inversion or empirical relationships is unable to generate stable retrievals. The use of information on input errors in the retrieval technique is necessary to generate solutions to the ill-posed problem. The MODIS operational LAI algorithm meets this requirement.
J. Geophys. Res. 01/2005; 110.
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[show abstract]
[hide abstract]
ABSTRACT: A small set of independent variables generally seems to suffice when attempting to describe the spectral response of a vegetation canopy to incident solar radiation. This set includes the soil reflectance, the single-scattering albedo, canopy transmittance, reflectance and interception, the portion of uncollided radiation in the total incident radiation, and portions of collided canopy transmittance and interception. All of these are measurable; they satisfy a simple system of equations and constitute a set that fully describes the law of energy conservation in vegetation canopies at any wavelength in the visible and near-infrared part of the solar spectrum. Further, the system of equations specifies the relationship between the optical properties at the leaf and the canopy scales. Thus, the information content of hyperspectral data can be fully exploited if these variables can be retrieved, for they can be more directly related to some of the physical properties of the canopy (e.g. leaf area index). This paper demonstrates this concept through retrievals of single-scattering albedo, canopy absorptance, portions of uncollided and collided canopy transmittance, and interception from hyperspectral data collected during a field campaign in Ruokolahti, Finland, June 14 -- 21, 2000. The retrieved variables are then used to estimate canopy leaf area index, vegetation ground cover, and also the ratio of direct to total incident solar radiation at blue, green, red, and near-infrared spectral intervals.
05/2003;
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Yuhong Tian,
Curtis E. Woodcock,
Yujie Wang,
Jeff L. Privette,
Nikolay V. Shabanov,
Liming Zhou,
Yu Zhang,
Wolfgang Buermann,
Jiarui Dong,
Brita Veikkanen,
Tuomas Hame,
Kaj Andersson,
Mutlu Ozdogan, Yuri Knyazikhin,
Ranga B. Myneni
[show abstract]
[hide abstract]
ABSTRACT: The development of appropriate ground-based validation techniques is critical to assessing uncertainties associated with satellite databased products. Here we present a method for validation of the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) product with emphasis on the sampling strategy for field data collection. This paper, the first of two-part series, details the procedures used to assess uncertainty of the MODIS LAI product. LAI retrievals from 30 m ETM+ data were first compared to field measurements from the SAFARI 2000 wet season campaign. The ETM+ based LAI map was thus as a reference to specify uncertainties in the LAI fields produced from MODIS data (250-, 500-, and 1000-m resolutions) simulated from ETM+. Because of high variance of LAI measurements over short distances and difficulties of matching measurements and image data, a patch-by-patch comparison method, which is more realistically implemented on a routine basis for validation, is proposed. Consistency between LAI retrievals from 30 m ETM+ data and field measurements indicates satisfactory performance of the algorithm. Values of LAI estimated from a spatially heterogeneous scene depend strongly on the spatial resolution of the image scene. The results indicate that the MODIS algorithm will underestimate LAI values by about 5% over the Maun site if the scale of the algorithm is not matched to the resolution of the data.
11/2002;
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[show abstract]
[hide abstract]
ABSTRACT: Ina recent paper [Landscape Ecol. 15: 591–601 (2000)] He et al. describedanaggregation index AI
i to measure pixelaggregation within a single class i. We show that thecommonly used shape index SI
i is related to theproposed aggregation metric as SI
i =(A
i) +AI
i(1 –(A
i)), with(A
i) dependent on class areaA
i only. Moreover, it is shown that thenormalized shape index, SI
i
*,equals (1 – AI
i). We conclude thatAI
i does not provide any information notprovided by SI
i, orSI
i
*.
Landscape Ecology 12/2001; 17(1):87-90. · 3.06 Impact Factor
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[show abstract]
[hide abstract]
ABSTRACT: This paper presents empirical and theoretical analyses of spectral hemispherical reflectances and transmittances of individual leaves and the entire canopy sampled at two sites representative of equatorial rainforests and temperate coniferous forests. The empirical analysis indicates that some simple algebraic combinations of leaf and canopy spectral transmittances and reflectances eliminate their dependencies on wavelength through the specification of two canopy-specific wavelength-independent variables. These variables and leaf optical properties govern the energy conservation in vegetation canopies at any given wavelength of the solar spectrum. The presented theoretical development indicates these canopy-specific wavelength-independent variables characterize the capacity of the canopy to intercept and transmit solar radiation under two extreme situations, namely, when individual leaves 1) are completely absorptive and 2) totally reflect and/or transmit the incident radiation. The interactions of photons with the canopy at red and near-infrared (IR) spectral bands approximate these extreme situations well. One can treat the vegetation canopy as a dynamical system and the canopy spectral interception and transmission as dynamical variables. The system has two independent states: canopies with totally absorbing and totally scattering leaves. Intermediate states are a superposition of these pure states. Such an interpretation provides powerful means to accurately specify changes in canopy structure both from ground-based measurements and remotely sensed data. This concept underlies the operational algorithm of global leaf area index (LAI), and the fraction of photosynthetically active radiation absorbed by vegetation developed for the moderate resolution imaging spectror...
04/2001;
