Hyperspectral remote sensing for shallow waters. I. A semianalytical model

Area of Science:

• Ocean optics
• Remote sensing science
• Coastal zone management

Background:

• Accurate shallow-water remote sensing requires separating water column and bottom signals.
• Previous models often incorrectly assumed equal diffuse attenuation coefficients.
• This distinction is crucial for retrieving bathymetry and optical properties.

Purpose of the Study:

• To develop a semianalytical model for shallow water remote sensing reflectance.
• To accurately model the separation of water column and bottom contributions.
• To improve retrieval of optical properties and bathymetry.

Main Methods:

• Utilized the Hydrolight radiative transfer model for simulations.
• Calculated remote-sensing reflectance (Rrs and rrs) under various conditions.
• Developed a semianalytical model expressing diffuse attenuation coefficients (K(d), K(u)(C), K(u)(B)) as functions of absorption (a) and backscattering (b(b)).

Main Results:

• The semianalytical model showed excellent agreement with Hydrolight simulations (~3% error).
• The model accurately performs even with varying particle phase functions and high turbidity (b(b)/a up to 1.5).
• Derived parameters for remote-sensing inversion connecting Rrs and rrs.

Conclusions:

• The developed semianalytical model provides a more accurate method for shallow-water remote sensing.
• It enables better separation of optical signals, leading to improved bathymetry and water property retrieval.
• This advancement is vital for coastal and optical remote sensing applications.