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Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval.
This yields a "population" permeability estimate, and requires considerable data reduction and advanced parameter estimation techniques to obtain mean biophysical parameter values.
This study provides insight into the assessment of canopy biophysical parameter retrieval using passive sensors and specifically into the quantification of tree height in a discontinuous canopy using a low-cost camera on board an unmanned aerial vehicle (UAV).
This sensitivity is attributed to negative estimate of a biophysical parameter that characterizes binding of internal Ca2+ to the uniporter.
Furthermore, the Case 2 is associated with negative estimates of the biophysical parameter αx (with αe = 0 fixed) (see Table S1), which is found to be contributing to the high sensitivities of the model predictions to variation in matrix [Ca2+].
As shown in Table S1, Case 2 is associated with negative estimates of the biophysical parameter αx (with αe = 0 fixed), which is found to be contributing to the high sensitivities of the model predictions to variation in matrix [Ca2+] and stiff gradients of Ca2+ uptake profiles to variation in ΔΨ.
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No circadian rhythmicity was found for the other biophysical parameters.
Fernandes, R. & Leblanc, S. G. Parametric (modified least squares) and non-parametric (Theil-Sen) linear regressions for predicting biophysical parameters in the presence of measurement errors.
Increasingly, more detailed pixel-wise estimates of forest biophysical parameters are needed for such endeavors.
Surface reflectance is usually the starting point for the retrieval of biophysical parameters from remote measurements.
This makes the method most suitable for both estimating biophysical parameters and monitoring vegetation phenology.
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