A research team has developed an improved semi-analytic Monte Carlo simulation method for bathymetric lidar that incorporates polarization sensitivity and describes complex water-column stratification more realistically. The work addresses a known limitation of conventional models, which tend to treat the aquatic medium as a homogeneous volume and neglect the polarization state of backscattered light, introducing biases in depth estimates in turbid or layered waters.

The method combines the flexibility of Monte Carlo simulations with a semi-analytic treatment that cuts computational cost compared with fully numerical approaches. By including polarization, the model captures how the scattering properties of particles and the seabed change with depth and viewing angle, better reproducing the signal returned by an airborne or shipborne lidar system over coastal waters, estuaries or zones with stratified suspended material.

The authors note that the improvement matters for bathymetric mapping in environments where turbidity varies with depth, a frequent scenario in freshwater-saltwater mixing zones or after runoff events. A more faithful simulation of the signal allows better tuning of the inversion algorithms that translate the laser echo into a depth measurement, and could reduce the uncertainty of lidar remote-sensing campaigns over complex waters.

The study falls within the field of applied optics and active remote sensing, where accurate modelling of laser pulse propagation in scattering media is key to calibrating instruments and planning survey flights. As next steps, validation of the model with field experimental data and its integration into operational processing chains of commercial or research bathymetric lidar systems could be expected.