Abstract

The three-dimensional radiative transfer model of Kimes [2] was used to extend our understanding of the physical principles causing the scattering dynamics in sparse vegetation canopies ( ≤50-percent ground cover). The model was upgraded by including an aniotropic scattering algorithm for soil developed by Walthall et al. [7]. The model was validated using measured directional reflectance data that covered the entire exitance hemisphere. Two canopies were chosen to present in this study-an orchard grass canopy (50-percent ground cover) and a hard wheat canopy (11-percent ground cover). These canopies showed the typical scattering behavior of canopies with low and intermediate vegetation density. A red wavelength (0.58-0.68 pm) band was used throughout the study. A number of phenomena contributed to the directional reflectance distributions observed in the field. These include: 1) the strong anisotropic scattering properties of the soil, 2) the geometric effect of the vegetation probability of gap function on the soil anisotropy and solar irradiance, and 3) the anisotropic scattering of vegetation which is controlled by the phase function (for an infinitely small volume of representative leaves) and geometric Effect 1 (cause by layering of leaves). These phenomena as identified in this paper account for the major scattering behavior of observed data sets of directional reflectance distributions. Such knowledge provides an intelligent basis for defining specifications of earth-observing sensor systems and for inferring important aspects of physical and biological processes of the plant system.

Keywords

Remote sensingScatteringVegetation (pathology)Environmental scienceRadiative transferCanopyBidirectional reflectance distribution functionIrradianceTree canopyAnisotropyOpticsGeologyPhysicsReflectivityGeography

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Publication Info

Year
1985
Type
article
Volume
GE-23
Issue
5
Pages
695-704
Citations
43
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D. S. Kimes, John M. Norman, C. L. Walthall (1985). Modeling the Radiant Transfers of Sparse Vegetation Canopies. IEEE Transactions on Geoscience and Remote Sensing , GE-23 (5) , 695-704. https://doi.org/10.1109/tgrs.1985.289388

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DOI
10.1109/tgrs.1985.289388