Article Type:
Research Article

Effects of Vegetation Clumping on Two–Source Model Estimates of Surface Energy Fluxes from an Agricultural Landscape during SMACEX

Martha C. Anderson Department of Soil Science, University of Wisconsin—Madison, Madison, Wisconsin

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J. M. Norman Department of Soil Science, University of Wisconsin—Madison, Madison, Wisconsin

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William P. Kustas Hydrology and Remote Sensing Laboratory, ARS, USDA, Beltsville, Maryland

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Fuqin Li Hydrology and Remote Sensing Laboratory, ARS, USDA, Beltsville, Maryland

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John H. Prueger National Soil Tilth Laboratory, Ames, Iowa

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John R. Mecikalski National Space Science and Technology Center, University of Alabama at Huntsville, Huntsville, Alabama

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Print Publication:
01 Dec 2005
DOI:
https://doi.org/10.1175/JHM465.1
Page(s):
892–909
Restricted access

Abstract

The effects of nonrandom leaf area distributions on surface flux predictions from a two-source thermal remote sensing model are investigated. The modeling framework is applied at local and regional scales over the Soil Moisture–Atmosphere Coupling Experiment (SMACEX) study area in central Iowa, an agricultural landscape that exhibits foliage organization at a variety of levels. Row-scale clumping in area corn- and soybean fields is quantified as a function of view zenith and azimuth angles using ground-based measurements of canopy architecture. The derived clumping indices are used to represent subpixel clumping in Landsat cover estimates at 30-m resolution, which are then aggregated to the 5-km scale of the regional model, reflecting field-to-field variations in vegetation amount. Consideration of vegetation clumping within the thermal model, which affects the relationship between surface temperature and leaf area inputs, significantly improves model estimates of sensible heating at both local and watershed scales in comparison with eddy covariance data collected by aircraft and with a ground-based tower network. These results suggest that this economical approach to representing subpixel leaf area hetereogeneity at multiple scales within the two-source modeling framework works well over the agricultural landscape studied here.

Corresponding author address: M. C. Anderson, 1525 Observatory Dr., University of Wisconsin—Madison, Madison, WI 53706. Email: mcanders@facstaff.wisc.edu

Abstract

The effects of nonrandom leaf area distributions on surface flux predictions from a two-source thermal remote sensing model are investigated. The modeling framework is applied at local and regional scales over the Soil Moisture–Atmosphere Coupling Experiment (SMACEX) study area in central Iowa, an agricultural landscape that exhibits foliage organization at a variety of levels. Row-scale clumping in area corn- and soybean fields is quantified as a function of view zenith and azimuth angles using ground-based measurements of canopy architecture. The derived clumping indices are used to represent subpixel clumping in Landsat cover estimates at 30-m resolution, which are then aggregated to the 5-km scale of the regional model, reflecting field-to-field variations in vegetation amount. Consideration of vegetation clumping within the thermal model, which affects the relationship between surface temperature and leaf area inputs, significantly improves model estimates of sensible heating at both local and watershed scales in comparison with eddy covariance data collected by aircraft and with a ground-based tower network. These results suggest that this economical approach to representing subpixel leaf area hetereogeneity at multiple scales within the two-source modeling framework works well over the agricultural landscape studied here.

Corresponding author address: M. C. Anderson, 1525 Observatory Dr., University of Wisconsin—Madison, Madison, WI 53706. Email: mcanders@facstaff.wisc.edu

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  • Anderson, M. C., Norman J. M. , Diak G. R. , Kustas W. P. , and Mecikalski J. R. , 1997: A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens. Environ., 60 , 195–216.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Anderson, M. C., Neale C. M. U. , Li F. , Norman J. M. , Kustas W. P. , Jayanthi H. , and Chavez J. , 2004a: Upscaling ground observations of vegetation water content, canopy height, and leaf area index during SMEX02 using aircraft and Landsat imagery. Remote Sens. Environ., 92 , 447–464.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Anderson, M. C., Norman J. M. , Mecikalski J. R. , Torn R. D. , Kustas W. P. , and Basara J. B. , 2004b: A multiscale remote sensing model for disaggregating regional fluxes to micrometeorological scales. J. Hydrometeor., 5 , 343–363.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Avissar, R., 1991: A statistical-dynamical approach to parameterize subgrid-scale land-surface heterogeneity in climate models. Surv. Geophys., 12 , 155–178.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Avissar, R., 1992: Conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models. J. Geophys. Res., 97D , 2729–2742.

    • Search Google Scholar
    • Export Citation

  • Avissar, R., and Pielke R. A. , 1989: A parameterization of heterogeneous land surface for atmospheric numerical models and its impact on regional meteorology. Mon. Wea. Rev., 117 , 2113–2136.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Berk, A., Bernstein L. S. , Anderson G. P. , Acharya P. K. , Robertson D. C. , Chetwynd J. H. , and Adler-Golden S. M. , 1998: MODTRAN cloud and multiple scattering upgrades with application to AVIRIS. Remote Sens. Environ., 65 , 367–375.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Blyth, E. M., 1995: Using a simple SVAT scheme to describe the effect of scale aggregation. Bound.-Layer Meteor., 72 , 267–285.

  • Bonan, G. B., Pollard D. , and Thompson S. L. , 1993: Influence of subgrid-scale heterogeneity in leaf area index, stomatal resistance, and soil moisture on grid-scale land-atmosphere interactions. J. Climate, 6 , 1882–1897.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Campbell, G. S., and Norman J. M. , 1998: An Introduction to Environmental Biophysics. Springer-Verlag, 286 pp.

  • Chen, J. M., 1996: Optically-based methods for measuring seasonal variation of leaf area index in boreal conifer stands. Agric. For. Meteor., 80 , 135–163.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chen, J. M., and Black T. A. , 1992: Defining leaf area index for non-flat leaves. Plant Cell Environ.,, 15 , 421–429.

  • Chen, J. M., and Cihlar J. , 1995: Quantifying the effect of canopy architecture on optical measurements of leaf area index using two gap size analysis methods. IEEE Trans. Geosci. Remote Sens., 33 , 777–787.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Chen, J. M., Liu J. , Leblanc S. G. , Lacaze R. , and Roujean J-L. , 2003: Multi-angular optical remote sensing for assessing vegetation structure and carbon absorption. Remote Sens. Environ., 84 , 516–525.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Choudhury, B. J., Ahmed N. U. , Idso S. B. , Reginato R. J. , and Daughtry C. S. T. , 1994: Relations between evaporation coefficients and vegetation indices studied by model simulations. Remote Sens. Environ., 50 , 1–17.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Diak, G. R., Bland W. L. , and Mecikalski J. R. , 1996: A note on first estimates of surface insolation from GOES-8 visible satellite data. Agric. For. Meteor., 82 , 219–226.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Diak, G. R., Bland W. L. , Mecikalski J. R. , and Anderson M. C. , 2000: Satellite-based estimates of longwave radiation for agricultural applications. Agric. For. Meteor., 103 , 349–355.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Doraiswamy, P. C., Hatfield J. L. , Jackson T. J. , Akhmedoc B. , Prueger J. , and Stern A. , 2004: Crop condition and yield simulations using Landsat and MODIS. Remote Sens. Environ., 92 , 548–559.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Eidenshink, J. C., 1992: The 1990 conterminous U.S. AVHRR data set. Photogr. Eng. Remote Sens., 58 , 809–813.

  • French, A. N., Norman J. M. , and Anderson M. C. , 2003: Simplified correction of GOES thermal infrared observations. Remote Sens. Environ., 87 , 326–333.

    • Search Google Scholar
    • Export Citation

  • Gao, B., 1996: NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens. Environ., 58 , 257–266.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Gillies, R. R., and Carlson T. N. , 1995: Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models. J. Appl. Meteor., 34 , 745–756.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Giorgio, F., and Avissar R. , 1997: Representation of heterogeneity effects in earth system modeling: Experience from land surface modeling. Rev. Geophys., 35 , 413–437.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Goudriaan, J., 1977: Crop Micrometeorology: A Simulation StudySimulation Monogr., Pudoc Center for Agricultural Publishing and Documentation, 249 pp.

  • Hansen, M. C., Defries R. S. , Townshend J. R. G. , and Sohlberg R. , 2000: Global land cover classification at 1 km spatial resolution using a classification tree approach. Int. J. Remote Sens., 21 , 1331–1364.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Jackson, T., Cosh M. , and Famiglietti J. , 2003: SMEX02 Iowa regional ground soil moisture data. National Snow and Ice Data Center, Digital Media. [Available online at http://nsidc.org/data/nsidc-0182.html.].

  • Koster, R., and Suarez M. , 1992a: A comparative analysis of two land surface heterogeneity representations. J. Climate, 5 , 1379–1390.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Koster, R., and Suarez M. , 1992b: Modeling the land surface boundary in climate models as a composite of independent vegetation stands. J. Geophys. Res., 97 , 2697–2715.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kucharik, C. J., Norman J. M. , Murdock L. M. , and Gower S. T. , 1997: Characterizing canopy nonrandomness with a Multiband Vegetation Imager (MVI). J. Geophys. Res., 102 , D24,. 29455–29473.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kucharik, C. J., Norman J. M. , and Gower S. T. , 1999: Characterization of radiation regimes in nonrandom forest canopies: Theory, measurements, and a simplified modeling approach. Tree Physiol., 19 , 695–706.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kustas, W. P., and Norman J. M. , 1997: A two-source approach for estimating turbulent fluxes using multiple angle thermal infrared observations. Water Resour. Res., 33 , 1495–1508.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kustas, W. P., and Norman J. M. , 1999a: Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover. Agric. For. Meteor., 94 , 13–25.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kustas, W. P., and Norman J. M. , 1999b: Reply to comments about the basic equations of dual-source vegetation-atmosphere transfer models. Agric. For. Meteor., 94 , 275–278.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kustas, W. P., and Norman J. M. , 2000a: Evaluating the effects of subpixel heterogeneity on pixel average fluxes. Remote Sens. Environ., 74 , 327–342.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kustas, W. P., and Norman J. M. , 2000b: A two-source energy balance approach using directional radiometric temperature observations for sparse canopy covered surfaces. Agron. J., 92 , 847–854.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Kustas, W. P., Hatfield J. L. , and Prueger J. H. , 2005: The Soil Moisture–Atmosphere Coupling Experiment (SMACEX): Background, hydrometeorological conditions, and preliminary findings. J. Hydrometeor., 6 , 791–804.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Lacaze, R., Chen J. M. , Roujean J-L. , and Leblanc S. G. , 2002: Retrieval of vegetation clumping index using hot spot signatures measured by POLDER instrument. Remote Sens. Environ., 79 , 84–95.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Li, F., Jackson T. J. , Kustas W. P. , Schmugge T. J. , French A. N. , Cosh M. , and Bindlish R. , 2004: Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX. Remote Sens. Environ., 92 , 521–534.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Li, F., Kustas W. P. , Prueger J. H. , Neale C. M. U. , and Jackson T. J. , 2005: Utility of remote sensing–based two-source energy balance model under low- and high-vegetation cover conditions. J. Hydrometeor., 6 , 878–891.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • MacPherson, J. I., and Wolde M. , 2002: NRC Twin Otter operations in the Soil Moisture-Atmosphere Coupling Experiment (SMACEX). National Research Council Canada Rep. LTR-FR-190, 91 pp.

  • MacPherson, J. I., Wolde M. , Kustas W. P. , and Prueger J. H. , 2003: Aircraft and tower-measured fluxes over rapidly growing corn and soybean crops in central Iowa. Preprints, 17th Conf. on Hydrology, Long Beach, CA, Amer. Meteor. Soc., CD-ROM, 3.1.

  • Mason, P. J., 1988: The formation of areally-averaged roughness lengths. Quart. J. Roy. Meteor. Soc., 114 , 399–420.

  • McNaughton, K. G., and Spriggs T. W. , 1986: A mixed-layer model for regional evaporation. Bound.-Layer Meteor., 74 , 262–288.

  • Mecikalski, J. M., Diak G. R. , Anderson M. C. , and Norman J. M. , 1999: Estimating fluxes on continental scales using remotely-sensed data in an atmosphere-land exchange model. J. Appl. Meteor., 38 , 1352–1369.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Nash, L. E., and Sutcliffe J. V. , 1970: River flow forecasting through conceptual models—Part 1: A discussion of principles. J. Hydrol., 10 , 282–290.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Neale, C. M. U., and Crowther B. G. , 1994: An airborne multispectral video/radiometer remote sensing system: Development and calibration. Remote Sens. Environ., 48 , 1–25.

    • Search Google Scholar
    • Export Citation

  • Nilson, T., 1971: A theoretical analysis of the frequency of gaps in plant stands. Agric. Meteor., 8 , 25–38.

  • Norman, J. M., and Becker F. , 1995: Terminology in thermal infrared remote sensing of natural surfaces. Remote Sens. Rev., 12 , 159–173.

  • Norman, J. M., Kustas W. P. , and Humes K. S. , 1995: A two-source approach for estimating soil and vegetation energy fluxes from observations of directional radiometric surface temperature. Agric. For. Meteor., 77 , 263–293.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Norman, J. M., and Coauthors, 2003: Remote sensing of surface energy fluxes at 101-m pixel resolutions. Water Resour. Res., 39 .1221, doi:10.1029/2002WR001775.

    • Search Google Scholar
    • Export Citation

  • Nouvellon, Y., Moran M. S. , Lo Seen D. , Rambal S. , Luquet D. , Chebouni G. , and Inoue Y. , 2000: PAR extinction in shortgrass ecosystems: Effects of clumping, sky conditions and soil albedo. Agric. For. Meteor., 105 , 21–41.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Otkin, J. A., Anderson M. C. , Mecikalski J. R. , and Diak G. R. , 2005: Validation of GOES-based insolation estimates using data from the United States Climate Reference Network. J. Hydrometeor.,, 6 , 460–475.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Priestley, C. H. B., and Taylor R. J. , 1972: On the assessment of surface heat flux and evaporation using large-scale parameters. Mon. Wea. Rev., 100 , 81–92.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Prueger, J. H., and Coauthors, 2005: Tower and aircraft eddy covariance measurements of water vapor, energy, and carbon dioxide fluxes during SMACEX. J. Hydrometeor.,, 6 , 954–960.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Roujean, J-L., and Lacaze R. , 2002: Global mapping of vegetation parameters from POLDER multiangular measurements for studies of surface-atmosphere interactions: A pragmatic method and its validation. J. Geophys. Res., 107 .4150, doi:10.1029/2001JD000751.

    • Search Google Scholar
    • Export Citation

  • Schuepp, P. H., Leclerc M. Y. , MacPherson J. I. , and Desjardins R. L. , 1990: Footprint prediction of scalar fluxes from analytical solutions of the diffusion equation. Bound.-Layer Meteor., 50 , 355–373.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Schuepp, P. H., MacPherson J. I. , and Desjardins R. L. , 1992: Adjustment of footprint correction for airborne flux mapping over the FIFE site. J. Geophys. Res., 97 , 18455–18466.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Twine, T. E., and Coauthors, 2000: Correcting eddy-covariance flux underestimates over a grassland. Agric. For. Meteor., 103 , 279–300.

  • Vining, R. C., and Blad B. L. , 1992: Estimation of sensible heat flux from remotely sensed canopy temperatures. J. Geophys. Res., 97 , D17,. 18951–18954.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Walthall, C., Dulaney W. , Anderson M. C. , Norman J. M. , Fang H. , and Liang S. , 2004: A comparison of empirical and neural network approaches for estimating corn and soybean leaf area index from Landsat ETM+ imagery. Remote Sens. Environ., 92 , 465–474.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Wieringa, J., 1986: Roughness-dependent geographical interpolation of surface wind speed averages. Quart. J. Roy. Meteor. Soc., 112 , 867–889.

  • Wilson, K., and Coauthors, 2002: Energy balance closure at FLUXNET sites. Agric. For. Meteor., 113 , 223–243.

  • Zhan, X., Kustas W. P. , and Humes K. S. , 1996: An intercomparison study on models of sensible heat flux over partial canopy surfaces with remotely sensed surface temperatures. Remote Sens. Environ., 58 , 242–256.

    • Crossref
    • Search Google Scholar
    • Export Citation
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