Estimating aboveground biomass (AGB) from variables resulting from electromagnetic radiation in the visible, near-infrared, and short-wavelength infrared (optical remote sensing and light detection and ranging—LiDAR) and in the microwave (synthetic aperture radar—SAR) remains a challenge. With the advancement of orbital LiDAR and SAR sensors in the L and P bands (e.g., ALOS PalSAR, NISAR, and BIOMASS), a promising new era begins, in which estimated accuracies increasingly approximate those of ground-based measurements. A comprehensive review of the physical principles is presented underlying the estimation of vegetation structure and AGB from remotely acquired SAR, optical, and LiDAR data used in ecological and carbon assessments. It also presents approaches for validating these estimates by comparing them with field data. Final considerations are provided regarding the applications, limitations, perspectives, and practical recommendations for using these technologies to estimate mangrove vegetation parameters from remotely sensed data.