Research Papers

Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at regional scales

[+] Author Affiliations
Rasmus Houborg

Earth System Science Interdisciplinary Center/Hydrological Sciences Branch, University of Maryland/NASA GSFC, 8800 Greenbelt Rd, Greenbelt, MD 20771

Martha C. Anderson

USDA-ARS Hydrology and Remote Sensing Lab., Beltsville, MD, Bldg 007 Rm 102, BARC-West, Beltsville, MD 20705

J. Appl. Remote Sens. 3(1), 033529 (May 7, 2009). doi:10.1117/1.3141522
History: Received December 15, 2008; Revised April 2, 2009; Accepted April 30, 2009; May 7, 2009
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Open Access Open Access

Abstract

This paper describes a novel physically-based approach for estimating leaf area index (LAI) and leaf chlorophyll content (Cab>) at regional scales that relies on radiance data acquirable from a suite of aircraft and operational satellite sensors. The REGularized canopy reFLECtance (REGFLEC) modeling tool integrates leaf optics (PROSPECT), canopy reflectance (ACRM), and atmospheric radiative transfer (6SV1) model components, facilitating the direct use of at-sensor radiances in green, red and near-infrared wavelengths. REGFLEC adopts a multi-step LUT-based inversion approach and incorporates image-based techniques to reduce the confounding effects of land cover specific vegetation parameters and soil reflectance. REGFLEC was applied to agricultural and natural vegetation areas using 10 m and 20 m resolution SPOT imagery, and variable environmental and plant development conditions allowed for model validation over a wide range in LAI (0 - 6) and Cab> (20 - 75 μg cm-2>). Validation against in-situ measurements yielded relative root-mean-square deviations on the order of 13% (0.4) for LAI and between 11 - 19% (4.9 - 9.1 μg cm-2) for Cab>. REGFLEC demonstrated good utility in detecting spatial and temporal variations in LAI and Cab without requiring site-specific data for calibration. The physical approach presented here can quite easily be applied to other regions and has the potential of being more universally applicable than traditional empirical approaches for retrieving LAI and Cab>.

References

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© 2009 Society of Photo-Optical Instrumentation Engineers

Citation

Rasmus Houborg and Martha C. Anderson
"Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at regional scales", J. Appl. Remote Sens. 3(1), 033529 (May 7, 2009). ; http://dx.doi.org/10.1117/1.3141522


Figures

Tables

References

G. B. Bonan, "Land-atmosphere interactions for climate system models: coupling biophysical, biogeochemical, and ecosystem dynamical processes," Rem. Sens. Environ. 51, 57-73 (1995)
R. M. Houborg and H. Soegaard (2004), "Regional simulation of ecosystem CO2> and water vapour exchange for agricultural land using NOAA AVHRR and Terra MODIS satellite data. Application to Zealand, Denmark," Rem. Sens. Environ. 93, 150-167 (2004)
S. M. Moran, S. J. Maas, and P. J. Pinter Jr., "Combining remote sensing and modeling for estimating surface evaporation and biomass production," Rem. Sens. Reviews 12, 335- 353 (1995).
J. M. Norman, W. P. Kustas, and K. S. Humes, "A two-source approach for estimating soil and vegetation energy fluxes from observations of directional radiometric surface temperature," Agric. For. Meteorol. 77, 263-293 (1995)
E. Boegh, H. Soegaard, N. Broge, C. B. Hasager, N. O. Jensen, K. Schelde, and A. Thomsen, "Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture," Rem. Sens. Environ. 81, 179-193 (2002)
I. Nijs, T. Behaeghe, and I. Impens, "Leaf nitrogen content as a predictor of photosynthetic capacity in ambient and global change conditions," J. Biogeogr. 22, 177-183 (1995)
G. A. Carter, "Ratios of leaf reflectances in narrow wavebands as indicators of plant stress," Int. J. Rem. Sens. 15, 697-704 (1994)
J. Penuelas and I. Filella, "Visible and near-infrared reflectance techniques for diagnosing plant physiological status," Trends Plant Sci. 3, 151-156 (1998)
P. J. Zarco-Tejada, J. R. Miller, G. H. Mohammed, T. L. Noland, and P. H. Sampson, "Vegetation stress detection through chlorophyll a+b estimation and fluorescence effects on hyperspectral imagery," J. Environ. Qual. 31, 1433-1441 (2002).
R. Houborg, M. Anderson, and C. Daughtry, "Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at the field scale," Rem. Sens. Environ. 113, 259-274 (2009)
C. S. T. Daughtry, C. K. Walthall, M. S. Kim, E. Brown de Costoun, and J. E. McMurtrey III, "Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance," Rem. Sens. Environ. 74, 229-239 (2000)
I. Filella, L. Serrano, J. Serra, and J. Penuelas, "Evaluating wheat nitrogen status with canopy reflectance indices and discriminant analysis," Crop Sci. 35, 1400-1405 (1995).
B. J. Yoder and R. E. Pettigrew-Crosby, "Predicting nitrogen and chlorophyll concentrations from reflectance spectra (400 - 2500 nm) at leaf and canopy scales," Rem. Sens. Environ. 49, 81-91 (1995)
A. A. Gitelson, A. Vina, S. B. Verma, D. C. Rundquist, T. J. Arkebauer, G. Keydan, B. Leavitt, V. Ciganda, G. G. Burba, and A. Suyker, "Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity," J. Geophys. Res. 111, D08S11, (2006)
Y. Yi, D. Yang, J. Huang, and D. Chen, "Evaluation of MODIS surface reflectance products for wheat leaf area index (LAI) retrieval," ISPRS J. Photogramm. 63, 661-677 (2008)
N. H. Broge and J. V. Mortensen, "Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data," Rem. Sens. Environ. 81, 45-57 (2002)
T. N. Carlson and D. A. Ripley, "On the relation between NDVI, fractional vegetation cover, and leaf area index," Rem. Sens. Environ. 62, 241- 252 (1997)
R. B. Myneni, S. Maggion, J. Iaquinta, J. L. Privette, N. Gobron, B. Pinty, D. S. Kimes, M. M. Verstraete, and D. L. Williams, " Optical remote sensing of vegetation: Modeling, caveats, and algorithms," Rem. Sens. Environ. 51, 169-188 (1995)
C. J. Tucker, "Remote sensing of leaf water content in the near infrared," Rem. Sens. Environ. 10, 23-32 (1980)
F. Baret and G. Guyot, "Potentials and limits of vegetation indices for LAI and APAR assessment," Rem. Sens. Environ. 35, 161-173 (1991)
R. Colombo, D. Bellingeri, D. Fasolini, and C. M. Marino, "Retrieval of leaf area index in different vegetation types using high resolution satellite data," Rem. Sens. Environ. 86, 120-131 (2003)
N. Gobron, B. Pinty, and M. M. Verstraete, "Theoretical limits to the estimation of the leaf area index on the basis of visible and near-infrared remote sensing data," IEEE T. Geosci. Rem. Sens. 35, 1438-1445 (1997)
R. Houborg, H. Soegaard, and E. Boegh, "Combining vegetation index and model inversion methods for the extraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data," Rem. Sens. Environ. 106, 39-58 (2007)
Y. J. Kaufman, D. D. Herring, K. J. Ranson, and G. J. Collatz, "Earth observing system AM1 mission to earth," IEEE T. Geosci. Rem. Sens. 36, 1045-1055 (1998)
A. Berk, G. P. Anderson, P. K. Acharya, L. S. Bernstein, L. Muratov, J. Lee, M. Fox, S. M. Adler-Golden, J. H. Chetwynd, M. L. Hoke, R. B. Lockwood, J. A. Gardner, T. W. Cooley, C. C. Borel, and P. E. Lewis, "MODTRAN 5: a reformulated atmospheric band model with auxiliary species and practical multiple scattering options: update," Proc. SPIE 5806, 662-667 (2005)
S. Y. Kotchenova and E. F. Vermote, "Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part II: Homogeneous Lambertian and anisotropic surfaces," Appl. Opt. 46, 4455-4464 (2007)
B. N. Holben, D. Tanre, A. Smirnov, T. F. Eck, I. Slutsker, N. Abuhassan, W. W. Newcomb, J. S. Schafer, B. Chatenet, F. Lavenu, Y. J. Kaufman, J. V. Castle, A. Setzer, B. Markham, D. Clark, R. Frouin, R. Halthore, A. Karneli, N. T. O'Neill, C. Pietras, R. T. Pinker, K. Voss, and G. Zibordi, "An emerging ground-based aerosol climatology: Aerosol optical depth from AERONET," J. Geophys. Res. 106, 12067-12097 (2001)
E. F. Vermote, N. Z. El Saleous, and C. O. Justice, "Atmospheric correction of MODIS data in the visible to middle infrared: first results," Rem. Sens. Environ. 83, 97 - 111 (2002)
S. Jacquemoud, F. Baret, B. Andrieu, F. M. Danson, and K. Jaggard, "Extraction of vegetation biophysical parameters by Inversion of the PROSPECT + SAIL models on sugar beet canopy reflectance data. Application to TM and AVIRIS sensors," Rem. Sens. Environ. 52, 163-172 (1995)
S. Jacquemoud, C. Bacour, H. Poilve, and J.-P. Frangi, "Comparison of Four Radiative Transfer Models to Simulate Plant Canopies Reflectance: Direct and Inverse Mode," Rem. Sens. Environ. 74, 471-481 (2000)
B. Combal, F. Baret, M. Weiss, A. Trubuil, D. Mace, A. Pragnere, R. Myneni, Y. Knyazikhin, and L. Wang, "Retrieval of canopy biophysical variables from bidirectional reflectance using prior information to solve the ill-posed inverse problem," Rem. Sens. Environ. 84, 1-15 (2002)
Y. Knyazikhin, J. V. Martonchik, D. J. Diner, R. B. Myneni, M. Verstraete, B. Pinty, and N. Gobron, "Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere-corrected MISR data," J. Geophys. Res. 103 (D24), 32239-32256 (1998)
M. Weiss, F. Baret, R. B. Myneni, A. Pragnere, and Y. Knyazikhin, "Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data," Agronomie 20, 3-22 (2000)
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