Retrieval of forest parameters using a fractal-based coherent scattering model and a genetic algorithm

In this paper, a procedure for retrieval of forest parameters is developed using the recently developed fractal-based coherent scattering model (FCSM) and a stochastic optimization algorithm. Since the fractal scattering mode l is computationally extensive, first a simplified empirical model with hig h fidelity for a desired forest stand is constructed using FCSM, Inputs to the empirical model are the influential structural and electrical parameter s of the forest stand, such as the tree density, tree height, trunk diamete r, branching angle, wood moisture, and soil moisture. Other finer structura l features are embedded in the fractal model. The model outputs are the pol arimetric and interferometric response of the forest as a function of the i ncidence angle. In this study, a genetic algorithm (GA) is employed as a gl obal search routine to characterize the input parameters of a forest stand from a set of measured polarimetric/interferometric backscatter responses o f the stand. The success of the inversion algorithm is demonstrated using a set of measured single-polarized interferometric synthetic aperture radar (SAR) data and several FCSM simulation results.