The mSCOPE model: A simple adaptation to the SCOPE model to describe reflectance, fluorescence and photosynthesis of vertically heterogeneous canopies

Yang, Peiqi; Verhoef, W.; Tol, Christiaan van der

doi:10.1016/j.rse.2017.08.029

Cited by 78 publications

(92 citation statements)

References 38 publications

(67 reference statements)

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“…The impact on the observed R and fluxes is 758 unclear, and further research is needed in this direction. In such studies, senSCOPE could also be 759 extended to other versions of SCOPE, such as mSCOPE (Yang et al 2017) to describe the vertical 760 distribution of senescent matter. 761 f green is a critical parameter in senSCOPE, it strongly controls RTM and fluxes and increases equifinality 762 of the inverse problem.…”

Section: Discussionmentioning

confidence: 99%

senSCOPE: Modeling radiative transfer and biochemical processes in mixed canopies combining green and senescent leaves with SCOPE

Pacheco‐Labrador

El-Madany

Tol

et al. 2020

Preprint

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Semi-arid grasslands and other ecosystems combine green and senescent leaves featuring different biochemical and optical properties, as well as functional traits. Knowing how these properties vary is necessary to understand the functioning of these ecosystems. However, differences between green and senescent leaves are not considered in recent models representing radiative transfer, heat, water and CO2 exchange such as the Soil-Canopy Observation of Photosynthesis and Energy fluxes (SCOPE). Neglecting the contribution of senescent leaves to the optical and thermal signal of vegetation limits the possibilities to use remote sensing information for studying these ecosystems; as well as neglecting their lack of photosynthetic activity increases uncertainty in the representation of ecosystem fluxes. In this manuscript we present senSCOPE as a step towards a more realistic representation of mixed green and senescent canopies. senSCOPE is a modified version of SCOPE model that describes a canopy combining green and senescent leaves with different properties and function. The model relies on the same numerical solutions than SCOPE, but exploits the linear nature of the scattering coefficients to combine optical properties of both types of leaf. Photosynthesis and transpiration only take place in green leaves; and different green and senescent leaf temperatures are used to close the energy balance. Radiative transfer of sun-induced fluorescence (SIF) and absorptance changes induced by the xanthophyll cycle action are also simulated. senSCOPE is evaluated against SCOPE both using synthetic simulations, forward simulations based on observations in a Mediterranean tree-grass ecosystem, and inverting dataset of ground measurements of reflectance factors, SIF, thermal radiance and gross primary production on a heterogeneous and partly senescent Mediterranean grassland. Results show that senSCOPE outputs vary quite linearly with the fraction of green leaf area, whereas SCOPE does not respond linearly to the effective leaf properties, calculated as the weighted average of green and senescent leaf parameters. Inversion results and pattern-oriented model evaluation show that senSCOPE improves the estimation of some parameters, especially chlorophyll content, with respect SCOPE retrievals during the dry season. Nonetheless, inaccurate knowledge of the optical properties of senescent matter still complicates model inversion. senSCOPE brings new opportunities for the monitoring of canopies mixing green and senescent leaves, and for improving the characterization of the optical properties of senescent material.

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Section: Discussionmentioning

confidence: 99%

senSCOPE: Modeling radiative transfer and biochemical processes in mixed canopies combining green and senescent leaves with SCOPE

Pacheco‐Labrador

El-Madany

Tol

et al. 2020

Preprint

Self Cite

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“…Nowadays, some RTM simulate optical (e.g., PRI, SIF) and / or TIR signals related with plant photosynthesis taking place at leaf level (van der Tol et al, 2009;Vilfan et al, 2018;Yang et al, 2017;Hernández-Clemente et al, 2017). However, this 100 modeling is not informative of the physiological processes originating such signals.…”

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confidence: 99%

Combining hyperspectral remote sensing and eddy covariance data streams for estimation of vegetation functional traits

Pacheco‐Labrador

El‐Madany

Martín

et al. 2020

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Abstract. Remote Sensing (RS) has traditionally provided estimates of key biophysical properties controlling light interaction with the canopy (e.g., chlorophyll content (Cab) or leaf area index (LAI)). However, recent and upcoming developments in hyperspectral RS are expected to lead to a new generation of products such as vegetation functional traits that control leaf carbon and water gas exchange. This information is pivotal to improve our understanding and capability to predict biosphere-atmosphere fluxes at global scale. Yet, the retrieval of key functional traits such as maximum carboxylation rate (Vcmax) or the Ball-Berry stomatal sensitivity parameter (m) remains challenging, as they only have a weak and indirect influence on optical reflectance factors. Recently, the assimilation of different observations in coupled soil-vegetation-atmosphere transfer (SVAT) and radiative transfer models (RTM) is allowing Vcmax and m estimates; notably using the Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model. In this work we assess the potential of airborne and satellite emulated hyperspectral imagery jointly with eddy covariance (EC) data for the retrieval of functional traits. Specifically, we made use of time series of gross primary production (GPP) and thermal irradiance measured with net radiometers, together with 17 hyperspectral airborne images. The potential of satellite-borne sensors was tested with emulated EnMAP imagery from the airborne data. EnMAP was selected because of the availability of the emulator, and because is one of the foreseen hyperspectral satellite missions expected to contribute to a new generation of RS products. We estimated ecosystem functional traits by inverting the senSCOPE model, a novel version of SCOPE adapted to represent partly senescent canopies. The experiment takes place in a Mediterranean tree-grass ecosystem subject of a large scale manipulation experiment with nitrogen and nitrogen plus phosphorus, monitored by three EC towers. Parameter estimates and predicted fluxes were evaluated using both ground observations and pattern-oriented model evaluation approach. The method developed in this study provided robust estimates of functional and biophysical parameters for both airborne and synthetic EnMAP datasets. Cab and Vcmax estimates followed observed relationships with leaf nitrogen concentration; whereas m and predicted underlying water use efficiency showed expected relationships with discrimination of 13C isotope in leaves. Results prove that the inversion of coupled RTM-SVAT models against a combination of hyperspectral imagery (e.g., EnMAP), and time series of GPP and thermal irradiance provides reliable estimates of key functional parameters of vegetation that are robust to several sources of uncertainty. The forthcoming satellite hyperspectral missions combined with ecosystem station networks (e.g. Integrated Carbon Observation System (ICOS), NEON, FLUXNET, etc&#8230;), offers unique possibilities to characterize the spatiotemporal distribution of functional parameters relevant for terrestrial biosphere modeling.

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“…The conventional approach of sampling foliar material exclusively from the sunlit upper canopy has recently become a contentious approach in remote sensing vegetation canopies. Recent studies demonstrate that the vertical heterogeneity in leaf chlorophyll, water and dry matter content have a significant effect on canopy reflectance measured by remote sensing instruments (Wang and Li, 2013;Yang et al, 2017;Zhao et al, 2017). The vertical heterogeneity in leaf traits is known to affect reabsorption and scattering of radiation within vegetation canopies, and subsequently, the top of canopy reflectance measured by remote sensing instruments (Verhoef and Bach, 2007).…”

Section: Implications On Plant Traits Spectroscopymentioning

confidence: 99%

“…Results presented in the current study demonstrate that the position of a leaf affects the performance of the PROSPECT model and the retrieval of its input parameters. This observation implies that failure to account for the vertical heterogeneity in leaf traits between sunlit upper and shaded lower leaves together with their optical properties might introduce significant uncertainties in modelling canopy reflectance and retrieval of canopy traits (Li et al, 2018b;Yang et al, 2017). These results are particularly relevant to the vegetation spectroscopy community considering that the PROSPECT model is coupled with widely used canopy RTMs such as INFORM (Schlerf and Atzberger, 2006) and SAILH (Jacquemoud et al, 2009).…”

Section: Implications On Plant Traits Spectroscopymentioning

confidence: 99%

Quantitative remote sensing of essential biodiversity variables

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The mSCOPE model: A simple adaptation to the SCOPE model to describe reflectance, fluorescence and photosynthesis of vertically heterogeneous canopies

Cited by 78 publications

References 38 publications

senSCOPE: Modeling radiative transfer and biochemical processes in mixed canopies combining green and senescent leaves with SCOPE

senSCOPE: Modeling radiative transfer and biochemical processes in mixed canopies combining green and senescent leaves with SCOPE

Combining hyperspectral remote sensing and eddy covariance data streams for estimation of vegetation functional traits

Quantitative remote sensing of essential biodiversity variables

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