The use of remote sensing in light use efficiency based models of gross primary production: A review of current status and future requirements

doi:10.1016/j.scitotenv.2007.11.007

Science of The Total Environment

Volume 404, Issues 2–3, 15 October 2008, Pages 411-423

https://doi.org/10.1016/j.scitotenv.2007.11.007 Get rights and content

Abstract

Global estimation and monitoring of plant photosynthesis (known as Gross Primary Production — GPP) is a critical component of climate change research. Modeling of carbon cycling requires parameterization of the land surface, which, in a spatially continuous mode, is only possible using remote sensing. The increasing availability of high spectral resolution satellite observations with global coverage and high temporal frequency has allowed the scientific community to revisit a number of existing approaches for modeling GPP, and reassess the potential for using remotely sensed inputs. In this paper we examine the current status and future requirements of modeling global GPP thereby focusing on the light use efficiency approach which expresses GPP as product of the photosynthetically active radiation (PAR), the fraction of PAR being absorbed by the plant canopy (f_PAR) and the efficiency ɛ with which this absorbed PAR can be converted into biomass. The capacity of remote sensing to provide the critical input variables for this approach is reviewed and key issues are identified and discussed for future research.

Introduction

Terrestrial ecosystems absorb approximately 60 Gt of carbon annually through the physiological process of photosynthesis (Janzen, 2004), also referred to as Gross Primary Production (GPP) (Hamilton et al., 2002). Simultaneously, autotrophic and heterotrophic organisms release about the same amount of carbon back into the atmosphere thereby closing the terrestrial carbon cycle. As the estimated annual turnover between the atmosphere and terrestrial ecosystems is approximately 120 Gt, considerably greater than the amount of fossil fuel emissions (5 Gt), small alterations in the terrestrial carbon balance are likely to have a significant impact on atmospheric CO₂ concentrations. As a result, there is a need for a better understanding of the dynamics of carbon fluxes between biosphere and atmosphere to help quantifying potential changes due to increased atmospheric CO₂ rates (Comins and McMurtrie, 1993, Luo and Reynolds, 1999). Global monitoring and prediction of GPP over forested and agricultural environments is therefore an ultimate goal of Earth climate change research seeking universal, generic modelling approaches applicable across multiple biomes and a wide variety of vegetation types.

Modeling of carbon cycling requires parameterization of the land surface (Hall et al., 1995), which, in a spatially continuous mode and on a regularly basis, is only possible using remote sensing. Modeling GPP from remote sensing is largely based on the awareness that plant physiological properties are related to the biochemical composition of plant foliage, and that this composition is reflected in the spectral radiation properties of leaves. Since the launch of the first satellite based sensors in the 1970s the remote sensing community has been limited in the number and width of the spectral wavebands available, and observation frequencies of existing sensors were incapable of detecting the spatial and temporal variability of primary production of vegetation. Recently, the advent of high spectral resolution optical sensors, capable of detecting changes in leaf spectral properties with a high temporal frequency (Prince and Goward, 1995) has allowed the scientific community to revisit a number of existing approaches for modeling GPP, and reassess the potential for using remotely sensed inputs, with the ultimate aim of driving GPP models entirely from satellite based observations (Running et al., 2004, Rahman et al., 2005). This paper reviews the current status of determining GPP from remotely sensed inputs and addresses future requirements for developing remote sensing based models of the terrestrial carbon cycle, specifically on approaches based on the light use efficiency concept.

Section snippets

Light use efficiency based modeling of primary production

One of the most widely applied concepts for modeling GPP is the light use efficiency approach of Monteith, 1972, Monteith, 1977 (e.g. Prince, 1991, Goetz and Prince, 1999, Heinsch et al., 2002, Turner et al., 2003a, Turner et al., 2003b), which expresses GPP as the product of the absorbed photosynthetically active radiation (PAR) (μmol m^− 2 s^− 1), defined as absorbed solar radiation between 400–700 nm wavelength, and the efficiency, with which the absorbed PAR can be converted into biomass: $GPP = PAR$

Photosynthetically active radiation

While the extraterrestrial radiation budget and its wavelength distribution are well known and relatively constant, the terrestrial reception of PAR is altered by a dynamically changing atmosphere (Van Laake and Sanchez-Azofeifa, 2004). Atmospheric radiative transfer is driven by absorption, molecular (Raleigh) and particle (Mie) scattering effects attenuating the amount of solar radiation received by the earth surface (Szeicz, 1974, Rao, 1984, Baker and Frouin, 1987). Early estimates of broad

Validation approaches

Validation and operationalization of the light use efficiency approach is currently underway at a number of spatial and temporal scales. At the stand level, eddy covariance data (EC) exhibit a key role for studying the temporal and spatial variability of GPP (Turner et al., 2006). EC measurements facilitate continuous estimates of net carbon accumulation, also referred to as net ecosystem production (NEP), from flux towers measuring CO₂ mixing ratios of up and down-moving eddies (Baldocchi, 2003

Requirements and direction for future studies

The ability to acquire primary production from remotely sensed data has increased considerably over the last few decades. However, from the reviewed literature, it is apparent that accurate modeling of GPP over large areas remains an active area of research with issues remaining to be solved on the leaf, stand, and landscape level.

Acknowledgements

The anonymous reviewers are thanked for helpful insights and constructive comments on the manuscript. This research is partially funded by a DAAD postgraduate scholarship to Hilker and a NSERC Discovery grant to Coops.

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The use of remote sensing in light use efficiency based models of gross primary production: A review of current status and future requirements

Abstract

Introduction

Section snippets

Light use efficiency based modeling of primary production

Photosynthetically active radiation

Validation approaches

Requirements and direction for future studies

Acknowledgements

Remote Sens Environ

Sol Energy

Agric For Meteorol

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Biochim Biophys Acta

Trends Plant Sci

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Adv Ecol Res

Adv Space Res

Remote Sens Environ

Agric Ecosyst Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Remote Sens Environ

Comput Electron Agric

Remote Sens Environ

Remote Sens Environ

Agric For Meteorol

Remote Sens Environ

Agric Ecosyst Environ

Remote Sens Environ

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Plant Cell Environ

Remote sensing of heterogeneity in photosynthetic efficiency, electron transport and dissipation of excess light in Populus deltoides stands under ambient and elevated CO2 concentrations, and in a tropical forest canopy, using a new laser-induced fluorescence transient device

Glob Chang Biol

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Agron Glas

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Agron Glas

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Proc. Natl. Acad. Sci. U. S. A.

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Z Für Naturforsch C—a J Biosci

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Remote sensing of heterogeneity in photosynthetic efficiency, electron transport and dissipation of excess light in Populus deltoides stands under ambient and elevated CO₂ concentrations, and in a tropical forest canopy, using a new laser-induced fluorescence transient device