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- W2425871946 abstract "Polarimetric Synthetic Aperture Radar (PolSAR) data is sensitive to physical structure of agricultural crops. In line with this fact radiative transfer theory based backscattering models have been used to explain the complicated interaction between electromagnetic waves and vegetation canopy. However, high degree of computational complexity of such models causes challenging inversion process. In this study, sparse Polynomial Chaos Expansion (PCE) metamodel is used for the inversion and the evaluation of the Global Sensitivity Analysis (GSA) of the model parameters. Finally promising results have been obtained for the estimation of height and diameter of stalks, length and width of leaves and growth stages for X-band PolSAR data." @default.
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- W2425871946 date "2016-05-01" @default.
- W2425871946 modified "2023-09-25" @default.
- W2425871946 title "Using metamodels for agricultural monitoring" @default.
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- W2425871946 doi "https://doi.org/10.1109/siu.2016.7495730" @default.
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