The photochemical reflectance index [PRI] and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies a review and meta - analysis
Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon fluxes? Can this be done at le...
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| Formato: | Artículo |
| Lenguaje: | Inglés |
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| Acceso en línea: | http://ri.agro.uba.ar/files/intranet/articulo/2011Garbulsky.pdf LINK AL EDITOR. |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
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| 245 | 1 | 0 | |a The photochemical reflectance index [PRI] and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies |b a review and meta - analysis |
| 520 | |a Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon fluxes? Can this be done at leaf, canopy and ecosystem scales and at different temporal scales? Different approaches can be used to answer these questions. Among them, the Photochemical Reflectance Index [PRI] derived from narrow-band spectroradiometers is a spectral index increasingly being used as an indicator of photosynthetic efficiency. We examined and synthesized the scientific literature on the relationships between PRI and several ecophysiological variables across a range of plant functional types and ecosystems at the leaf, canopy and ecosystem levels and at the daily and seasonal time scales. Our analysis shows that although the strength of these relationships varied across vegetation types, levels of organization and temporal scales, in most reviewed articles PRI was a good predictor of photosynthetic efficiency or related variables with performances at least as good as the widely used NDVI as indicator of green biomass. There are possible confounding factors related to the intensity of the physiological processes linked to the PRI signals, to the structure of the canopies and to the illumination and viewing angles that warrant further studies, and it is expected that the utility of PRI will vary with the ecosystem in question due to contrasting environmental constraints, evolutionary strategies, and radiation use efficiency [RUE; the ratio between carbon uptake and light absorbed by vegetation] variability. Clearly, more research comparing ecosystem responses is warranted. Additionally, like any 2-band index that is affected by multiple factors, the interpretation of PRI can be readily confounded by multiple environmental variables, and further work is needed to understand and constrain these effects. Despite these limitations, this review shows an emerging consistency of the RUE-PRI relationship that suggests a surprising degree of functional convergence of biochemical, physiological and structural components affecting leaf, canopy and ecosystem carbon uptake efficiencies. PRI accounted for 42 percent, 59 percent and 62 percent of the variability of RUE at the leaf, canopy and ecosystem respective levels in unique exponential relationships for all the vegetation types studied. It seems thus that by complementing the estimations of the fraction of photosynthetically active radiation intercepted by the vegetation [FPAR], estimated with NDVI-like indices, PRI enables improved assessment of carbon fluxes in leaves, canopies and many of the ecosystems of the world from ground, airborne and satellite sensors. | ||
| 653 | 0 | |a GROSS PRIMARY PRODUCTIVITY | |
| 653 | 0 | |a MODIS | |
| 653 | 0 | |a PHOTOCHEMICAL REFLECTANCE INDEX | |
| 653 | 0 | |a BAND INDEX | |
| 653 | 0 | |a CARBON FLUXES | |
| 653 | 0 | |a CARBON UPTAKE | |
| 653 | 0 | |a ECOSYSTEM LEVELS | |
| 653 | 0 | |a ECOSYSTEM RESPONSE | |
| 653 | 0 | |a ENVIRONMENTAL CONSTRAINTS | |
| 653 | 0 | |a ENVIRONMENTAL VARIABLES | |
| 653 | 0 | |a EVOLUTIONARY STRATEGIES | |
| 653 | 0 | |a FRACTION OF PHOTOSYNTHETICALLY ACTIVE RADIATIONS | |
| 653 | 0 | |a GREEN PLANTS | |
| 653 | 0 | |a META-ANALYSIS | |
| 653 | 0 | |a MULTIPLE FACTORS | |
| 653 | 0 | |a NARROW BANDS | |
| 653 | 0 | |a PHOTOSYNTHETIC CAPACITY | |
| 653 | 0 | |a PHOTOSYNTHETIC EFFICIENCY | |
| 653 | 0 | |a PHYSIOLOGICAL PROCESS | |
| 653 | 0 | |a PLANT FUNCTIONAL TYPE | |
| 653 | 0 | |a RADIATION USE EFFICIENCY | |
| 653 | 0 | |a RELATED VARIABLES | |
| 653 | 0 | |a REMOTE SENSING TECHNIQUES | |
| 653 | 0 | |a SATELLITE SENSORS | |
| 653 | 0 | |a SCIENTIFIC LITERATURE | |
| 653 | 0 | |a SPECTRAL INDICES | |
| 653 | 0 | |a SPECTRO-RADIOMETERS | |
| 653 | 0 | |a STRUCTURAL COMPONENT | |
| 653 | 0 | |a TEMPORAL SCALE | |
| 653 | 0 | |a TIME-SCALES | |
| 653 | 0 | |a VEGETATION TYPE | |
| 653 | 0 | |a VIEWING ANGLE | |
| 653 | 0 | |a BIOMASS | |
| 653 | 0 | |a EVOLUTIONARY ALGORITHMS | |
| 653 | 0 | |a FORESTRY | |
| 653 | 0 | |a PHOTOSYNTHESIS | |
| 653 | 0 | |a PHYSIOLOGY | |
| 653 | 0 | |a PHYTOPLANKTON | |
| 653 | 0 | |a PRODUCTIVITY | |
| 653 | 0 | |a RADIOMETERS | |
| 653 | 0 | |a RATING | |
| 653 | 0 | |a REFLECTION | |
| 653 | 0 | |a REMOTE SENSING | |
| 653 | 0 | |a VEGETATION | |
| 653 | 0 | |a ECOSYSTEMS | |
| 653 | 0 | |a CARBON FLUX | |
| 653 | 0 | |a ECOPHYSIOLOGY | |
| 653 | 0 | |a ECOSYSTEM RESPONSE | |
| 653 | 0 | |a FUNCTIONAL GROUP | |
| 653 | 0 | |a LEAF | |
| 653 | 0 | |a LIGHT USE EFFICIENCY | |
| 653 | 0 | |a LITERATURE REVIEW | |
| 653 | 0 | |a META-ANALYSIS | |
| 653 | 0 | |a NDVI | |
| 653 | 0 | |a PHOTOCHEMISTRY | |
| 653 | 0 | |a PHOTOSYNTHESIS | |
| 653 | 0 | |a PHOTOSYNTHETICALLY ACTIVE RADIATION | |
| 653 | 0 | |a PHYTOMASS | |
| 653 | 0 | |a RADIOMETER | |
| 653 | 0 | |a REFLECTANCE | |
| 653 | 0 | |a REMOTE SENSING | |
| 653 | 0 | |a SATELLITE SENSOR | |
| 653 | 0 | |a VIRIDIPLANTAE | |
| 700 | 1 | |9 17762 |a Garbulsky, Martín Fabio | |
| 700 | 1 | |9 50629 |a Peñuelas, Josep | |
| 700 | 1 | |a Gamon, J. |9 69379 | |
| 700 | 1 | |a Inoue, Y. |9 69380 | |
| 700 | 1 | |9 66929 |a Filella, Iolanda | |
| 773 | |t Remote Sensing of Environment |g Vol.115, no.2 (2011), p.281-297 | ||
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| 900 | |a ^tThe photochemical reflectance index [PRI] and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies^sA review and meta-analysis | ||
| 900 | |a ^aGarbulsky^bM.F. | ||
| 900 | |a ^aPeñuelas^bJ. | ||
| 900 | |a ^aGamon^bJ. | ||
| 900 | |a ^aInoue^bY. | ||
| 900 | |a ^aFilella^bI. | ||
| 900 | |a ^aGarbulsky^bM. F. | ||
| 900 | |a ^aPeñuelas^bJ. | ||
| 900 | |a ^aGamon^bJ. | ||
| 900 | |a ^aInoue^bY. | ||
| 900 | |a ^aFilella^bI. | ||
| 900 | |a ^aGarbulsky, M.F.^tGlobal Ecology Unit, CREAF, CEAB, CSIC, Center for Ecological Research and Forestry Applications, Universitat Autónoma de Barcelona, 08193 Bellaterra, Catalunya, Spain | ||
| 900 | |a ^aPeñuelas, J.^tFaculty of Agronomy, Universidad de Buenos Aires, C1417DSE, Buenos Aires, Argentina | ||
| 900 | |a ^aGamon, J.^tDepartments of Earth and Atmospheric Sciences and Biological Sciences, University of Alberta, Edmonton T6G 2E3, Alberta, Canada | ||
| 900 | |a ^aInoue, Y.^tNational Institute for Agro-Environmental Sciences [NIAES] Tsukuba, Ibaraki 305-8604, Japan | ||
| 900 | |a ^aFilella, I.^t | ||
| 900 | |a ^tRemote Sensing of Environment^cRemote Sens. Environ. | ||
| 900 | |a en | ||
| 900 | |a 281 | ||
| 900 | |a ^i | ||
| 900 | |a Vol. 115, no. 2 | ||
| 900 | |a 297 | ||
| 900 | |a GROSS PRIMARY PRODUCTIVITY | ||
| 900 | |a MODIS | ||
| 900 | |a PHOTOCHEMICAL REFLECTANCE INDEX | ||
| 900 | |a BAND INDEX | ||
| 900 | |a CARBON FLUXES | ||
| 900 | |a CARBON UPTAKE | ||
| 900 | |a ECOSYSTEM LEVELS | ||
| 900 | |a ECOSYSTEM RESPONSE | ||
| 900 | |a ENVIRONMENTAL CONSTRAINTS | ||
| 900 | |a ENVIRONMENTAL VARIABLES | ||
| 900 | |a EVOLUTIONARY STRATEGIES | ||
| 900 | |a FRACTION OF PHOTOSYNTHETICALLY ACTIVE RADIATIONS | ||
| 900 | |a GREEN PLANTS | ||
| 900 | |a META-ANALYSIS | ||
| 900 | |a MULTIPLE FACTORS | ||
| 900 | |a NARROW BANDS | ||
| 900 | |a PHOTOSYNTHETIC CAPACITY | ||
| 900 | |a PHOTOSYNTHETIC EFFICIENCY | ||
| 900 | |a PHYSIOLOGICAL PROCESS | ||
| 900 | |a PLANT FUNCTIONAL TYPE | ||
| 900 | |a RADIATION USE EFFICIENCY | ||
| 900 | |a RELATED VARIABLES | ||
| 900 | |a REMOTE SENSING TECHNIQUES | ||
| 900 | |a SATELLITE SENSORS | ||
| 900 | |a SCIENTIFIC LITERATURE | ||
| 900 | |a SPECTRAL INDICES | ||
| 900 | |a SPECTRO-RADIOMETERS | ||
| 900 | |a STRUCTURAL COMPONENT | ||
| 900 | |a TEMPORAL SCALE | ||
| 900 | |a TIME-SCALES | ||
| 900 | |a VEGETATION TYPE | ||
| 900 | |a VIEWING ANGLE | ||
| 900 | |a BIOMASS | ||
| 900 | |a EVOLUTIONARY ALGORITHMS | ||
| 900 | |a FORESTRY | ||
| 900 | |a PHOTOSYNTHESIS | ||
| 900 | |a PHYSIOLOGY | ||
| 900 | |a PHYTOPLANKTON | ||
| 900 | |a PRODUCTIVITY | ||
| 900 | |a RADIOMETERS | ||
| 900 | |a RATING | ||
| 900 | |a REFLECTION | ||
| 900 | |a REMOTE SENSING | ||
| 900 | |a VEGETATION | ||
| 900 | |a ECOSYSTEMS | ||
| 900 | |a CARBON FLUX | ||
| 900 | |a ECOPHYSIOLOGY | ||
| 900 | |a ECOSYSTEM RESPONSE | ||
| 900 | |a FUNCTIONAL GROUP | ||
| 900 | |a LEAF | ||
| 900 | |a LIGHT USE EFFICIENCY | ||
| 900 | |a LITERATURE REVIEW | ||
| 900 | |a META-ANALYSIS | ||
| 900 | |a NDVI | ||
| 900 | |a PHOTOCHEMISTRY | ||
| 900 | |a PHOTOSYNTHESIS | ||
| 900 | |a PHOTOSYNTHETICALLY ACTIVE RADIATION | ||
| 900 | |a PHYTOMASS | ||
| 900 | |a RADIOMETER | ||
| 900 | |a REFLECTANCE | ||
| 900 | |a REMOTE SENSING | ||
| 900 | |a SATELLITE SENSOR | ||
| 900 | |a VIRIDIPLANTAE | ||
| 900 | |a Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon fluxes? Can this be done at leaf, canopy and ecosystem scales and at different temporal scales? Different approaches can be used to answer these questions. Among them, the Photochemical Reflectance Index [PRI] derived from narrow-band spectroradiometers is a spectral index increasingly being used as an indicator of photosynthetic efficiency. We examined and synthesized the scientific literature on the relationships between PRI and several ecophysiological variables across a range of plant functional types and ecosystems at the leaf, canopy and ecosystem levels and at the daily and seasonal time scales. Our analysis shows that although the strength of these relationships varied across vegetation types, levels of organization and temporal scales, in most reviewed articles PRI was a good predictor of photosynthetic efficiency or related variables with performances at least as good as the widely used NDVI as indicator of green biomass. There are possible confounding factors related to the intensity of the physiological processes linked to the PRI signals, to the structure of the canopies and to the illumination and viewing angles that warrant further studies, and it is expected that the utility of PRI will vary with the ecosystem in question due to contrasting environmental constraints, evolutionary strategies, and radiation use efficiency [RUE; the ratio between carbon uptake and light absorbed by vegetation] variability. Clearly, more research comparing ecosystem responses is warranted. Additionally, like any 2-band index that is affected by multiple factors, the interpretation of PRI can be readily confounded by multiple environmental variables, and further work is needed to understand and constrain these effects. Despite these limitations, this review shows an emerging consistency of the RUE-PRI relationship that suggests a surprising degree of functional convergence of biochemical, physiological and structural components affecting leaf, canopy and ecosystem carbon uptake efficiencies. PRI accounted for 42 percent, 59 percent and 62 percent of the variability of RUE at the leaf, canopy and ecosystem respective levels in unique exponential relationships for all the vegetation types studied. It seems thus that by complementing the estimations of the fraction of photosynthetically active radiation intercepted by the vegetation [FPAR], estimated with NDVI-like indices, PRI enables improved assessment of carbon fluxes in leaves, canopies and many of the ecosystems of the world from ground, airborne and satellite sensors. | ||
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