Fine-Tuning of Forest Height Retrieval in PolInSAR Using Population-Based Optimization

Abstract

In this study, we utilize the population-based optimization (PBO) techniques to accurately retrieve the forest height (FH) in polarimetric synthetic aperture radar interferometry (PolInSAR) inversion. After the initial FH information is obtained using conventional PolInSAR inversion methods, it is adjusted using the PBO techniques and two physical models, which are the random-volume-over ground (RVoG) and the simplified version of random-motion-over-ground (RMoG) models. The concept of fine-tuning was applied to both single-baseline (SB) and multibaseline (MB) PolInSAR data. In the results obtained using both the simulated and real data, the proposed fine-tuning approach exhibits significantly improved FH estimation results, as compared with the conventional inversions.