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Title: Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil

Abstract

An analytical model of the bidirectional reflectance for optically semi-infinite plant canopies has been extended to describe the reflectance of finite depth canopies with contributions from the underlying soil. The model depends on 10 independent parameters describing vegetation and soil optical and structural properties. The model is inverted with a nonlinear minimization routine using directional reflectance data for lawn (leaf area index (LAI) is equal to 9.9), soybeans (LAI, 2.9) and simulated reflectance data (LAI, 1.0) from a numerical bidirectional reflectance distribution function (BRDF) model (Myneni et al.). While the ten-parameter model results in relatively low rms differences for the BRDF, most of the retrieved parameters exhibit poor stability. Sensitivity tests were performed to determine which of the 10 parameters were most important and to assess the effects of Gaussian noise on the parameter retrievals. Out of the 10 parameters, three were identified which described most of the BRDF variability. At low LAI value the most influential parameters were the single-scattering albedos (both soil and vegetation) and LAI, while at higher LAI values (>2.5) these shifted to the two scattering phase function parameters for vegetation and the single-scattering albedo of the vegetation. The three-parameter model, formed by fixing the sevenmore » least significant parameters, gave higher rms values but less sensitive to noise in the BRDF than the full ten-parameter model. A full hemispherical reflectance data set for lawn was then interpolated to yield BRDF values corresponding to advanced very high resolution radiometer (AVHRR) scan geometries collected over a period of nine days. The resulting retrieved parameters and BRDFs are similar to those for the full sampling geometry, suggesting that the limited geometry of AVHRR measurements might be used to reliably retrieve BRDF and canopy albedo with this model. 18 refs., 12 figs., 7 tabs.« less

Authors:
 [1];  [2];  [3]
  1. Univ. of Hamburg (Germany)
  2. Univ. of Arizona, Tuscon, AZ (United States)
  3. Univ. of Colorado, Boulder, CO (United States); and others
Publication Date:
OSTI Identifier:
166201
Resource Type:
Journal Article
Journal Name:
Journal of Geophysical Research
Additional Journal Information:
Journal Volume: 99; Journal Issue: D5; Other Information: PBD: 20 May 1994
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; GRAMINEAE; SPECTRAL REFLECTANCE; MATHEMATICAL MODELS; SOILS; ANALYTICAL SOLUTION; SENSITIVITY ANALYSIS

Citation Formats

Schluessel, G, Dickinson, R E, and Privette, J L. Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil. United States: N. p., 1994. Web. doi:10.1029/94JD00481.
Schluessel, G, Dickinson, R E, & Privette, J L. Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil. United States. https://doi.org/10.1029/94JD00481
Schluessel, G, Dickinson, R E, and Privette, J L. 1994. "Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil". United States. https://doi.org/10.1029/94JD00481.
@article{osti_166201,
title = {Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil},
author = {Schluessel, G and Dickinson, R E and Privette, J L},
abstractNote = {An analytical model of the bidirectional reflectance for optically semi-infinite plant canopies has been extended to describe the reflectance of finite depth canopies with contributions from the underlying soil. The model depends on 10 independent parameters describing vegetation and soil optical and structural properties. The model is inverted with a nonlinear minimization routine using directional reflectance data for lawn (leaf area index (LAI) is equal to 9.9), soybeans (LAI, 2.9) and simulated reflectance data (LAI, 1.0) from a numerical bidirectional reflectance distribution function (BRDF) model (Myneni et al.). While the ten-parameter model results in relatively low rms differences for the BRDF, most of the retrieved parameters exhibit poor stability. Sensitivity tests were performed to determine which of the 10 parameters were most important and to assess the effects of Gaussian noise on the parameter retrievals. Out of the 10 parameters, three were identified which described most of the BRDF variability. At low LAI value the most influential parameters were the single-scattering albedos (both soil and vegetation) and LAI, while at higher LAI values (>2.5) these shifted to the two scattering phase function parameters for vegetation and the single-scattering albedo of the vegetation. The three-parameter model, formed by fixing the seven least significant parameters, gave higher rms values but less sensitive to noise in the BRDF than the full ten-parameter model. A full hemispherical reflectance data set for lawn was then interpolated to yield BRDF values corresponding to advanced very high resolution radiometer (AVHRR) scan geometries collected over a period of nine days. The resulting retrieved parameters and BRDFs are similar to those for the full sampling geometry, suggesting that the limited geometry of AVHRR measurements might be used to reliably retrieve BRDF and canopy albedo with this model. 18 refs., 12 figs., 7 tabs.},
doi = {10.1029/94JD00481},
url = {https://www.osti.gov/biblio/166201}, journal = {Journal of Geophysical Research},
number = D5,
volume = 99,
place = {United States},
year = {Fri May 20 00:00:00 EDT 1994},
month = {Fri May 20 00:00:00 EDT 1994}
}