A New FAPAR Analytical Model Based on the Law of Energy Conservation: A Case Study in China

The fraction of absorbed photosynthetically active radiation (FAPAR) characterizes the energy-absorption ability of the vegetation canopy. It is a critical input to many land-surface models such as crop growth models, net primary productivity models, and climate models. There is a great need for FAPAR products derived from remote-sensing data. The objective of this research is to develop a new instantaneous quantitative FAPAR model based on the law of energy conservation and the concept of recollision probability (p). Using the ray-tracing method, the FAPAR-P model separates direct energy absorption by the canopy from energy absorption caused by multiple scattering between the soil and the canopy. Direct sunlight and diffuse skylight are also considered. This model has a clear physical meaning and can be applied to continuous and discrete vegetation. The model was validated by Monte Carlo (MC) simulation and field measurements in the Heihe River basin, China, which proved its reliability for FAPAR calculations.

[1]  C. Field,et al.  A reanalysis using improved leaf models and a new canopy integration scheme , 1992 .

[2]  Hervé Sinoquet,et al.  RATP: a model for simulating the spatial distribution of radiation absorption, transpiration and photosynthesis within canopies: application to an isolated tree crown , 2001 .

[3]  Elizabeth M. Middleton,et al.  Variations of Foliage Chlorophyll fAPAR and Foliage Non-Chlorophyll fAPAR (fAPAR$_{\rm chl}$, fAPAR$_{\rm non\mathchar "702D chl}$) at the Harvard Forest , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[4]  S. Running,et al.  Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active , 1998 .

[5]  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..

[6]  Dennis D. Baldocchi,et al.  Scaling carbon dioxide and water vapour exchange from leaf to canopy in a deciduous forest. II. Model testing and application , 1995 .

[7]  Dennis D. Baldocchi,et al.  Measuring and modelling carbon dioxide and water vapour exchange over a temperate broad‐leaved forest during the 1995 summer drought , 1997 .

[8]  Ray Leuning,et al.  A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy. II. Comparison with measurements , 1998 .

[9]  S. Goward,et al.  Global Primary Production: A Remote Sensing Approach , 1995 .

[10]  R. Leuning,et al.  A two-leaf model for canopy conductance, photosynthesis and partitioning of available energy I:: Model description and comparison with a multi-layered model , 1998 .

[11]  Jan Pisek,et al.  Algorithm for global leaf area index retrieval using satellite imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[12]  E. Kowalczyk,et al.  Implementation of a soil-canopy scheme into the CSIRO GCM -- regional aspects of the model response , 1994 .

[13]  H. G. Jerrard.  Advanced remote sensing: Edited by R.G. Nishinaga SPIE Proceedings, Volume 363, 1983, pp v + 156, $49 , 1984 .

[14]  S. T. Gower,et al.  Leaf area index of boreal forests: theory, techniques, and measurements , 1997 .

[15]  R. Fensholt,et al.  Evaluation of MODIS LAI, fAPAR and the relation between fAPAR and NDVI in a semi-arid environment using in situ measurements , 2004 .

[16]  N. Gobron,et al.  The MERIS Global Vegetation Index (MGVI): Description and preliminary application , 1999 .

[17]  J. Garratt.  Sensitivity of Climate Simulations to Land-Surface and Atmospheric Boundary-Layer Treatments-A Review , 1993 .

[18]  E. S. Page.  The Monte Carlo Method: The Method of Statistical Trials , 1967 .

[19]  Wenjie Fan,et al.  A unified canopy bidirectional reflectance (BRDF) model for row ceops , 2012, Science China Earth Sciences.

[20]  T. Nilson.  A theoretical analysis of the frequency of gaps in plant stands , 1971 .

[21]  PuechClaude,et al.  Plant models faithful to botanical structure and development , 1988 .

[22]  J. Chen.  Optically-based methods for measuring seasonal variation of leaf area index in boreal conifer stands , 1996 .

[23]  N. Metropolis,et al.  The Monte Carlo method. , 1949 .

[24]  D. Pury,et al.  Simple scaling of photosynthesis from leaves to canopies without the errors of big‐leaf models , 1997 .

[25]  Marc Jaeger,et al.  Plant models faithful to botanical structure and development , 1988, SIGGRAPH.

[26]  A. Dalcher,et al.  A Simple Biosphere Model (SIB) for Use within General Circulation Models , 1986 .

[27]  Allison L. Dunn,et al.  A satellite‐based biosphere parameterization for net ecosystem CO2 exchange: Vegetation Photosynthesis and Respiration Model (VPRM) , 2008 .

[28]  Jean Dauzat,et al.  Simulation of leaf transpiration and sap flow in virtual plants: model description and application to a coffee plantation in Costa Rica. , 2001 .

[29]  Ann Henderson-Sellers,et al.  Biosphere-atmosphere Transfer Scheme (BATS) for the NCAR Community Climate Model , 1986 .

[30]  A. Bondeau,et al.  Comparing global models of terrestrial net primary productivity (NPP): analysis of differences in light absorption and light‐use efficiency , 1999 .

[31]  N. Gobron,et al.  A semidiscrete model for the scattering of light by vegetation , 1997 .

[32]  D. Baldocchi,et al.  CO2 fluxes over plant canopies and solar radiation: a review , 1995 .

[33]  Suan Chin Wong,et al.  A simple calibrated model of Amazon rainforest productivity based on leaf biochemical properties , 1995 .

[34]  Michael L. Goulden,et al.  Testing a Mechanistic Model of Forest-Canopy Mass and Energy Exchange Using Eddy Correlation: Carbon Dioxide and Ozone Uptake by a Mixed Oak-Maple Stand , 1994 .

[35]  N. Gobron,et al.  Evaluation of the MERIS/ENVISAT FAPAR product , 2007 .

[36]  Gérard Dedieu,et al.  Spatial and temporal variability of land CO2 fluxes estimated with remote sensing and analysis data over western Eurasia , 2002 .

[37]  Frédéric Baret,et al.  Validation of global moderate-resolution LAI products: a framework proposed within the CEOS land product validation subgroup , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[38]  Gregory P. Asner,et al.  SCALE DEPENDENCE OF ABSORPTION OF PHOTOSYNTHETICALLY ACTIVE RADIATION IN TERRESTRIAL ECOSYSTEMS , 1998 .

[39]  C. E. Murphy,et al.  Development and Evaluation of Simplified Models for Simulating Canopy Photosynthesis and Transpiration , 1976 .

[40]  N. Gobron,et al.  Uncertainty Estimates for the FAPAR Operational Products Derived from MERIS - Impact of Top-of-Atmosphere Radiance Uncertainties and Validation with Field Data , 2008 .

[41]  O. Hagolle,et al.  LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm , 2007 .

[42]  P. Stenberg,et al.  Simple parameterizations of the radiation budget of uniform broadleaved and coniferous canopies , 2005 .

[43]  W. Fan,et al.  Accurate LAI retrieval method based on PROBA/CHRIS data. , 2009 .

[44]  T. Andrew Black,et al.  Assessing FPAR source and parameter optimization scheme in application of a diagnostic carbon flux model , 2009 .

[45]  Nadine Gobron,et al.  A global vegetation index for SeaWiFS: Design and applications , 2001 .

[46]  D. Turner,et al.  Integrating Remote Sensing and Ecosystem Process Models for Landscape- to Regional-Scale Analysis of the Carbon Cycle , 2004 .

[47]  Dianna Hogan,et al.  Advanced Remote Sensing Research , 2008 .

[48]  D. Randall,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation , 1996 .

[49]  W. Cohen,et al.  Evaluation of fraction of absorbed photosynthetically active radiation products for different canopy radiation transfer regimes: methodology and results using Joint Research Center products derived from SeaWiFS against ground-based estimations. , 2006 .

[50]  Philip Lewis,et al.  A spectral invariant approach to modelling canopy and leaf scattering , 2005 .

[51]  S. Gower,et al.  Spatial and temporal validation of the MODIS LAI and FPAR products across a boreal forest wildfire chronosequence , 2013 .

[52]  Ü. Rannik,et al.  Gap filling strategies for defensible annual sums of net ecosystem exchange , 2001 .

[53]  K. Hibbard,et al.  A Global Terrestrial Monitoring Network Integrating Tower Fluxes, Flask Sampling, Ecosystem Modeling and EOS Satellite Data , 1999 .

[54]  Terhikki Manninen,et al.  Simulation of the effect of snow covered forest floor on the total forest albedo , 2009 .

[55]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .