Water content estimation in vegetation with MODIS reflectance data and model inversion methods
Introduction
Quantitative estimation of leaf biochemical and canopy biophysical variables is a key element to the successful application of remote sensing in vegetation monitoring, a major goal in terrestrial ecology and a long-term research objective given the complexity of the vegetation canopies and phenomena Goetz et al., 1992, Verstraete et al., 1994. Accurate estimates of leaf pigments, nitrogen, dry matter, water content, and leaf area index (LAI) from remote sensing can assist in determining vegetation physiological status Carter, 1994, Peñuelas et al., 1994, the study of species and seasonal dependence (e.g., Belanger, Miller, & Boyer, 1995), and may serve as bioindicators of vegetation stress (e.g., Luther & Carroll, 1999, Zarco-Tejada et al., 2001). The remote determination of one of these biochemical constituents, vegetation water content, has important implications in agriculture and forestry (Gao & Goetz, 1995), it is essential for drought assessment in natural vegetation (Peñuelas, Filella, Biel, Serrano, & Savé, 1993), and it is a major driver in predicting the susceptibility to fire Chandler et al., 1983, Pyne et al., 1996, Ustin et al., 1998.
Several studies demonstrate the existing link between leaf-level reflectance in the 400–2500 nm spectral region and the amount of water in the leaf through optical indices, regression analysis and radiative transfer modeling Aldakheel & Danson, 1997, Allen et al., 1971, Carter, 1991, Carter, 1993, Ceccato et al., 2001, Danson et al., 1992, Gausman et al., 1970, Hunt et al., 1987, Jacquemoud & Baret, 1990. The primary and secondary effects of water content on leaf reflectance were studied by Carter (1991) showing that sensitivity of leaf reflectance to water content was greatest in spectral bands centered at 1450, 1940, and 2500 nm. Indirect effects of water content on reflectance were also found at 400 nm, in the red edge at 700 nm (Filella & Peñuelas, 1994) and on vegetation indices such as NDVI (Roberts, Green, & Adams, 1997). The effects of leaf structure on the water absorption bands were studied by Danson et al. (1992) showing that derivative reflectance calculated in the water absorption features minimized the effects due to leaf structure, therefore maximizing the sensitivity to leaf water content. Lately, the broad use of leaf radiative transfer models such as PROSPECT (Jacquemoud & Baret, 1990) for broadleaf species, LIBERTY (Dawson, Curran, & Plummer, 1998) based on radiative transfer characterization in needles, and LEAFMOD (Ganapol, Johnson, Hammer, Hlavka, & Peterson, 1998) among others, enable the simulation of the leaf optical properties as a function of leaf structural and biochemical constituents such as chlorophyll a+b (Ca+b), dry matter (Cm), and leaf equivalent water thickness (Cw).
Several research efforts focus on the application of leaf-level indices calculated from water-absorption bands, statistical relationships between leaf reflectance and leaf water content, and scaling-up methods to canopy level through radiative transfer simulation. As an example, airborne visible infrared imaging spectrometer (AVIRIS) imagery was used to derive equivalent water thickness in vegetation using nonlinear and linear least squares spectral matching techniques, achieving good agreements with ground measured leaf fuel moisture (LFM) content (Gao & Goetz, 1995). In other studies, Pinzón, Ustin, Castañeda, and Smith (1998) and Ustin et al. (1998) using hierarchical foreground/background analysis (HFBA) showed general success retrieving equivalent water thickness by radiative transfer modeling using the 960-nm absorption band, but breaking down for low LAI canopies due to the increasing effects of soil background and shadows on sparse vegetation. Other ratios, such as the plant water index (PWI, R970/R900) (Peñuelas, Piñol, Ogaya, & Filella, 1997) was used to map vegetation water content with AVIRIS imagery, but found to be affected not only by water content, but also by canopy structure and viewing geometry (Serrano, Ustin, Roberts, Gamon, & Peñuelas, 2000) therefore highly dependent on bi-directional and geometrical effects of the vegetation canopy. The normalized difference water index (NDWI) calculated as (R860−R1240)/(R860+R1240) was suggested by Gao (1996) in a theoretical study, demonstrating its potential applicability for canopy-level water content estimation based on the liquid water absorption band centered at 1240 nm enhanced by canopy scattering. Nevertheless, Zarco-Tejada and Ustin (2001) showed in a simulation study the dependency of NDWI and the simple ratio water index (SRWI, R858/R1240) on leaf-level variables such as leaf structure and dry matter content, and most importantly, on canopy LAI.
These partially successful results, obtained when estimating vegetation water content, demonstrate the need for modeling efforts to account for leaf and canopy variables and the viewing geometry. Efforts to investigate the successful scaling up of optical indices from leaf to canopy level through radiative transfer simulation Haboudane et al., 2002, Zarco-Tejada et al., 1999, Zarco-Tejada et al., 2001 show the importance of these methods when estimating leaf biochemical constituents from canopy reflectance data. Nevertheless, few investigations are found which apply these radiative transfer methods and model inversion techniques for leaf water content estimation from canopy reflectance imagery. Examples are the simulation studies to estimate equivalent water thickness by model inversion by Jacquemoud, Baret, Andrieu, Danson, and Jaggard (1995), Jacquemoud et al. (1996) and Fourty and Baret (1997) linking the PROSPECT leaf model (Jacquemoud & Baret, 1990) and SAIL canopy model (Verhoef, 1984), showing successful retrievals of Cw from continuous hyperspectral (AVIRIS-simulated) and multispectral (TM-simulated) spectra taking into account leaf- and canopy-level variables. Recently, Ceccato, Flasse, and Grégoire (2002) and Ceccato, Gobron, Flasse, Pinty, and Tarantola (2002) developed an optical index for SPOT-VEGETATION sensor based on global sensitivity analysis using radiative transfer models.
The work presented here investigates the applicability of these radiative transfer techniques to MODIS reflectance data for vegetation water content estimation. A simulation study with synthetic spectra and MODIS-equivalent reflectance is presented, investigating the spectral capabilities of MODIS for estimating leaf equivalent water thickness by inversion of a linked leaf–canopy model. Further, a seasonal field study was undertaken for leaf sampling and analysis of LFM content from 10 study sites, measuring fresh and dry weight of leaf samples. Time-series of MODIS reflectance spectra from the study sites during the period of the field experiment were used for model inversion to estimate equivalent water thickness by radiative transfer simulation.
Section snippets
Modeling the effects of water content on MODIS-equivalent reflectance
Willstatter and Stoll (1913) presented the earliest description of a theory to explain the leaf optical properties, with subsequent improvements and development of new leaf models: Allen and Richardson (1968); Breece and Holmes (1971); Woolley (1971); Allen, Gausman, Richardson, and Thomas (1969), Allen, Gayle and Richarson (1970). Allen and Richardson (1968) applied the Kubelka–Munk (K–M) theory (Kubelka & Munk, 1931) to study the interaction of light with stacked plant leaves, relating leaf
Field sampling study and results for Cw estimation from MODIS data
A field sampling campaign was conducted for the analysis of LFM content, measuring fresh and dry weight from leaf samples collected in 10 study sites of chaparral vegetation in California (USA) between March and September, 2000. Data collection was conducted as part of research to study spatially explicit models of fire spread through chaparral fuels (Morais, 2001). MODIS reflectance data were obtained for the same period of field data acquisition, and inversion methods conducted linking
Conclusion
Simulation methods and results from the modeling and field studies described in this article demonstrate that leaf water content can be globally monitored with MODIS reflectance data by radiative transfer modeling. Optical indices previously suggested in the literature as potential indicators of vegetation water content, such as SRWI and NDWI, were used in a simulation study with linked leaf–canopy models. Leaf- and canopy-level variables such as leaf structure, dry matter content, soil
Acknowledgements
This work was supported by NASA contract NAG5-9360 Incorporating New EOS Data Products into Models to Improve Estimates of Biogeochemical Processes. The authors gratefully acknowledge M. Marais and D. Roberts (University of California, Santa Barbara) and C. Lee (California State University, Long Beach) for their contribution in the leaf data used in this study. W. Verhoef and S. Jacquemoud are gratefully acknowledged for providing computer code for leaf and canopy reflectance models; B.-C. Gao
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