Estimating light absorption by chlorophyll, leaf and canopy in a deciduous broadleaf forest using MODIS data and a radiative transfer model

• Published in: Remote sensing of environment Vol. 99; no. 3; pp. 357 - 371
• Main Authors: Zhang, Qingyuan, Xiao, Xiangming, Braswell, Bobby, Linder, Ernst, Baret, Fred, Moore, Berrien
• Format: Journal Article
• Language: English
• Published: New York, NY Elsevier Inc 30-11-2005; Elsevier Science
• Subjects: Animal, plant and microbial ecology; Applied geophysics; Biological and medical sciences; Earth sciences; Earth, ocean, space; Exact sciences and technology; FAPAR; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Internal geophysics; Markov Chain Monte Carlo (MCMC) method; MODIS; PROSPECT; SAIL-2; Teledetection and vegetation maps; MODIS; PROSPECT; SAIL-2; FAPAR; Markov Chain Monte Carlo (MCMC) method; algorithms; Deciduous forest; Spectroradiometry; Spectral band; vegetation; Probability distribution; MCMC algorithm; photosynthesis; imagery; Procedure; Radiative transfer; models; inverse problem; Photosynthetically active radiation; Space remote sensing; chlorophyll; Plant leaf; Biophysics; forests; FAPAR: Markov Chain Monte Carlo (MCMC) method; temperate zone; biochemistry; primary productivity; Canopy(vegetation)
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2005.09.009

In this paper, we present a theoretical and modeling framework to estimate the fractions of photosynthetically active radiation (PAR) absorbed by vegetation canopy (FAPAR
canopy), leaf (FAPAR
leaf ), and chlorophyll (FAPAR
chl), respectively. FAPAR
canopy is an important biophysical variable and has been used to estimate gross and net primary production. However, only PAR absorbed by chlorophyll is used for photosynthesis, and therefore there is a need to quantify FAPAR
chl. We modified and coupled a leaf radiative transfer model (PROSPECT) and a canopy radiative transfer model (SAIL-2), and incorporated a Markov Chain Monte Carlo (MCMC) method (the Metropolis algorithm) for model inversion, which provides probability distributions of the retrieved variables. Our two-step procedure is: (1) to retrieve biophysical and biochemical variables using coupled PROSPECT
+
SAIL-2 model (PROSAIL-2), combined with multiple daily images (five spectral bands) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor; and (2) to calculate FAPAR
canopy, FAPAR
leaf and FAPAR
chl with the estimated model variables from the first step. We evaluated our approach for a temperate forest area in the Northeastern US, using MODIS data from 2001 to 2003. The inverted PROSAIL-2 fit the observed MODIS reflectance data well for the five MODIS spectral bands. The estimated leaf area index (LAI) values are within the range of field measured data. Significant differences between FAPAR
canopy and FAPAR
chl are found for this test case. Our study demonstrates the potential for using a model such as PROSAIL-2, combined with an inverse approach, for quantifying FAPAR
chl, FAPAR
leaf, FAPAR
canopy, biophysical variables, and biochemical variables for deciduous broadleaf forests at leaf- and canopy-levels over time.