Rapid estimation of bathymetry from multispectral imagery without in situ bathymetry data

Area of Science:

• Remote Sensing
• Oceanography
• Coral Reef Ecology

Background:

• Optimization-based semi-analytical methods (OSMs) and empirical methods (EMs) are used for bathymetry mapping from satellite data, crucial for coral reef management.
• OSMs require iterative computations but no in situ data, while EMs are fast but need in situ measurements.
• A need exists for rapid bathymetry estimation from satellite data without in situ measurements.

Purpose of the Study:

• To develop a novel empirical method for rapid bathymetry estimation from multispectral satellite data.
• To combine the strengths of an optimization-based method (unmixing-based multispectral optimization process exemplar method - UMOPE) and an empirical method (Stumpf's ratio method - SRM).
• To enable bathymetry mapping without requiring in situ data.

Main Methods:

• A new empirical method was developed by integrating UMOPE with SRM.
• Regression parameters for SRM were determined using reflectance values from sampled pixels and corresponding water depths estimated by UMOPE.
• The method was validated using WorldView-2 (WV-2a, WV-2b) and Landsat 8 imagery of the Xisha Islands.

Main Results:

• The new method performed comparably to SRM for Landsat 8 and WV-2b data, showing similar root mean square errors across different depths.
• The absence of a coastal band in WV-2a imagery led to increased errors in deeper waters, particularly with noisy reflectance data.
• The method's accuracy is dependent on the regression line between UMOPE-estimated and measured depths being close to the 1:1 line.

Conclusions:

• The combined UMOPE-SRM method offers a viable approach for rapid bathymetry estimation without in situ data.
• The method shows promise for utilizing free Landsat 8 data for bathymetry mapping in optically shallow waters globally.
• Future applications can benefit from this technique for efficient coral reef monitoring and management.