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

Abstract The vertical heterogeneity of leaf biophysical and biochemical properties may have a large effect on the bidirectional reflectance and fluorescence of vegetation canopies. This has implications for the interpretation of remote sensing data. We developed a model for light interaction and energy balance in vegetation canopies in which leaf biophysical and biochemical properties vary in the vertical. The model mSCOPE is an extension of the Soil-Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model, which simulates spectral and bidirectional reflectance, fluorescence, and photosynthesis of vertically heterogeneous vegetation canopies. The modelling of radiative transfer in mSCOPE is based on the classical SAIL theory. A solution to the radiative transfer equation for multi-layer canopies is given, which allows calculating top-of-canopy (TOC) reflectance and the flux profile. The latter is used for the simulation of fluorescence emission and photosynthesis of every leaf through the leaf radiative transfer model Fluspect and a biochemical model. The radiative transfer of fluorescence in multi-layer canopies is solved numerically in mSCOPE to obtain TOC bidirectional fluorescence. The significant effect of vertical heterogeneity of leaf properties on TOC reflectance, fluorescence and photosynthesis is demonstrated by different scenarios with customized vertical profiles of leaf chlorophyll content and leaf water content, and also with measured vertical profiles of leaf chlorophyll content in corn canopies. A preliminary validation of the reflectance calculating routine of mSCOPE is conducted by comparing measured and simulated TOC reflectance spectra of the corn canopies. We conclude that it is important to consider the vertical heterogeneity of leaf properties for the prediction of reflectance, fluorescence and photosynthesis. The model mSCOPE could serve as a tool to better understand vertically heterogeneous vegetation canopies.

[1]  J. Cihlar,et al.  Plant canopy gap-size analysis theory for improving optical measurements of leaf-area index. , 1995, Applied optics.

[2]  W. Verhoef,et al.  Coupled soil–leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data , 2007 .

[3]  D. Pitts,et al.  Reflectance of a vegetation canopy using the Adding method. , 1982, Applied optics.

[4]  R. Houborg,et al.  Combining vegetation index and model inversion methods for the extraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data , 2007 .

[5]  R. Rabbinge,et al.  Dynamics of Vertical Leaf Nitrogen Distribution in a Vegetative Wheat Canopy. Impact on Canopy Photosynthesis , 2000 .

[6]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[7]  Matthijs Tollenaar,et al.  Vertical Profile of Leaf Senescence during the Grain‐Filling Period in Older and Newer Maize Hybrids , 2004 .

[8]  M. Schaepman,et al.  Far-red sun-induced chlorophyll fluorescence shows ecosystem-specific relationships to gross primary production: An assessment based on observational and modeling approaches , 2015 .

[9]  W. Verhoef,et al.  A model and measurement comparison of diurnal cycles of sun-induced chlorophyll fluorescence of crops , 2016 .

[10]  W. Verhoef.  Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model , 1984 .

[11]  Jean-Luc Widlowski,et al.  Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models , 2007 .

[12]  Yubin Lan,et al.  Effect of Vertical Distribution of Crop Structure and Biochemical Parameters of Winter Wheat on Canopy Reflectance Characteristics and Spectral Indices , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[13]  A. R. Nascimento,et al.  Canopy openness and lai estimates in two seasonally deciduous forests on limestone outcrops in central Brazil using hemispherical photographs , 2007 .

[14]  Lu Li,et al.  Remote Estimation of Leaf and Canopy Water Content in Winter Wheat with Different Vertical Distribution of Water-Related Properties , 2015, Remote. Sens..

[15]  A. Gitelson,et al.  Three‐band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves , 2006 .

[16]  R. Myneni.  Modeling radiative transfer and photosynthesis in three-dimensional vegetation canopies , 1991 .

[17]  S. Ustin,et al.  Estimation of tree canopy leaf area index by gap fraction analysis , 1993 .

[18]  James A. Gardner,et al.  MODTRAN5: a reformulated atmospheric band model with auxiliary species and practical multiple scattering options , 2004, SPIE Asia-Pacific Remote Sensing.

[19]  Michel M. Verstraete,et al.  Raytran: a Monte Carlo ray-tracing model to compute light scattering in three-dimensional heterogeneous media , 1998, IEEE Trans. Geosci. Remote. Sens..

[20]  J. Berry,et al.  A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species , 1980, Planta.

[21]  A. Gitelson,et al.  Vertical profile and temporal variation of chlorophyll in maize canopy: Quantitative "crop vigor" indicator by means of reflectance-based techniques , 2008 .

[22]  V. Demarez,et al.  Modeling radiative transfer in heterogeneous 3D vegetation canopies , 1995, Remote Sensing.

[23]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[24]  Wout Verhoef,et al.  The FLuorescence EXplorer Mission Concept—ESA’s Earth Explorer 8 , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[25]  N. Baker.  Chlorophyll fluorescence: a probe of photosynthesis in vivo. , 2008, Annual review of plant biology.

[26]  G. Collatz,et al.  Coupled Photosynthesis-Stomatal Conductance Model for Leaves of C4 Plants , 1992 .

[27]  J. Berry,et al.  Models of fluorescence and photosynthesis for interpreting measurements of solar-induced chlorophyll fluorescence , 2014, Journal of geophysical research. Biogeosciences.

[28]  W. Verhoef,et al.  An integrated model of soil-canopy spectral radiances, photosynthesis, fluorescence, temperature and energy balance , 2009 .

[29]  W. Verhoef.  Theory of radiative transfer models applied in optical remote sensing of vegetation canopies , 1998 .

[30]  W. Verhoef,et al.  Fluspect-B: a model for leaf fluorescence, reflectance and transmittance spectra. , 2016 .

[31]  Michael E. Schaepman,et al.  Retrieval of foliar information about plant pigment systems from high resolution spectroscopy , 2009 .

[32]  W. Verhoef.  Earth observation modelling based on layer scattering matrices , 1984 .

[33]  A. Huete,et al.  Estimation of vegetation photosynthetic capacity from space‐based measurements of chlorophyll fluorescence for terrestrial biosphere models , 2014, Global change biology.

[34]  Ahmad Al Bitar,et al.  DART: Recent Advances in Remote Sensing Data Modeling With Atmosphere, Polarization, and Chlorophyll Fluorescence , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[35]  Pingheng Li,et al.  Canopy vertical heterogeneity plays a critical role in reflectance simulation , 2013 .

[36]  R. Colombo,et al.  Sun‐induced fluorescence – a new probe of photosynthesis: First maps from the imaging spectrometer HyPlant , 2015, Global change biology.

[37]  C. Wit.  Space relationships within populations of one or more species , 1962 .

[38]  C. T. Wit.  Photosynthesis of leaf canopies , 1965 .

[39]  Yuri A. Gritz,et al.  Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. , 2003, Journal of plant physiology.

[40]  A. Kuusk.  A two-layer canopy reflectance model , 2001 .

[41]  Luis Alonso,et al.  Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications , 2009 .