Neural network approach for correction of multiple scattering errors in the LISST-VSF instrument
Optics Express
|October 20, 2023
Summary
A new neural network corrects errors in volume scattering function (VSF) measurements caused by multiple scattering in turbid waters. This method improves accuracy for instruments like the LISST-VSF, enhancing underwater optical applications.
Area of Science:
- Ocean Optics
- Optical Instrumentation
- Data Science
Background:
- The LISST-VSF instrument measures volume scattering function (VSF) and attenuation in natural waters, crucial for remote sensing and underwater communications.
- High particle concentrations in turbid waters cause significant errors in LISST-VSF measurements due to multiple scattering.
- These errors affect derived optical properties like scattering coefficient and phase function, limiting instrument reliability.
Purpose of the Study:
- To develop a method for correcting multiple scattering errors in LISST-VSF measurements.
- To improve the accuracy of VSF and derived optical properties in turbid natural waters.
Main Methods:
- A feedforward neural network was developed to correct VSF errors using only measured VSF data as input.
- The neural network was trained using Monte Carlo simulations of the LISST-VSF across a range of scattering coefficients (0.05-50 m⁻¹).
- The model was validated using VSF measurements from natural water samples.
Main Results:
- The neural network accurately estimated VSFs, closely matching expected values without multiple scattering errors in both angular shape and magnitude.
- For a natural water sample with an expected scattering coefficient of 10.6 m⁻¹, the error in the scattering coefficient was reduced from 103% to 5%.
- The approach significantly reduced uncertainties in VSF and derived properties for LISST-VSF measurements in turbid waters.
Conclusions:
- A neural network approach effectively corrects multiple scattering errors in LISST-VSF measurements.
- This method enhances the reliability and accuracy of optical measurements in turbid aquatic environments.
- The improved accuracy supports broader applications in remote sensing, environmental monitoring, and underwater optical communications.
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