Layer Model with Random Spheroidal Scatterers for Remote Sensing of Vegetation Canopy

Abstract

A layer model is developed and applied to interpret radar backscattering coefficients at 5.3 GHz for a soybean canopy. The canopy is modeled as a random medium containing spheroidal scatterers for the leaves. The data were taken over an extended time period from early to late stage of the vegetation. The theoretical results and the experimental data are in good agreement. The lateral correlation length is observed to be highly correlated with the canopy fractional volume. With consideration of the interrelations among biophysical parameters, the model is then used to simulate backscattering coefficients under various conditions. The results provide sensitivity domains of radar responses to soil moisture and vegetation biomass for inversion assessment. Furthermore, the polarization signatures of the vegetation canopy are synthesized to illustrate structural information conveyed by polarimetric data.