Abstract
This study introduces derivations of the soil isoline equation for the case of partial canopy coverage. The derivation relied on extending the previously derived soil isoline equations, which assumed full canopy coverage. This extension was achieved by employing a two-band linear mixture model, in which the fraction of vegetation cover (FVC) was considered explicitly as a biophysical parameter. A parametric form of the soil isoline equation, which accounted for the influence of the FVC, was thereby derived. The differences between the soil isolines of the fully covered and partially covered cases were explored analytically. This study derived the approximated isoline equations for nine cases defined by the choice of the truncation order in the parametric form. A set of numerical experiments was conducted using coupled leaf and canopy radiative transfer models. The numerical results revealed that the accuracy of the soil isoline increased with the truncation order, and they confirmed the validity of the derived expressions.
Highlights
Satellite observations of the earth’s surface have been crucial for estimating biophysical and geophysical parameters used in a wide range of environmental studies.[1]
This study extends the previously derived soil isoline equations in the red–NIR subspace derived for the case of full canopy coverage
Because the model used the fraction of vegetation cover (FVC) parameter explicitly in its formulation, we were able to derive the parametric form of the soil isoline equations using the FVC
Summary
Satellite observations of the earth’s surface have been crucial for estimating biophysical and geophysical parameters used in a wide range of environmental studies.[1] Estimation algorithms often involve algebraic manipulations of multispectral reflectance maps to provide scaler values that are strongly correlated with physical parameters.[2,3,4] The spectral vegetation index (VI)[4,5,6] is an example of an algebraic manipulation used routinely for a variety of purposes over several decades These band manipulations have provided rich information from remotely sensed satellite imagery. The final step is the approximation of soil isoline equations as relationships between the red and NIR reflectances of the original space by truncating the order of the common parameter. The accuracy of the derived isoline depends on the truncation orders of the two bands
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