Bathymetry maps of ocean islands are important for both safe navigation and scientific studies. Thesemaps can be generated from different data sources and using different methods. In-water ship-basesurveying, is one of the known methods known to produce the most accurate depth information but islimited to deep-water areas. High-resolution multispectral satellite imagery allows mapping ofunderwater features that are not accessible to surveying vessels. Many models have been developed toextract water depth from multispectral imagery. These models, although have been successfullyapplied in various applications, have been shown to perform poorly in optically shallow waters withheterogeneous bottom types and varying albedo. This project proposes to develop linear and nonlinearmulti-spectral bathymetric models in order to utilize high-resolution WorldView-2 multi-spectralimages to generate accurate and complete bathymetric maps of shallow water areas in the study sizelocated in South China Sea. Because the bandwidth of WorldView-2 imagery is relatively wide,which will increase the uncertainty of the model parameters and derivation, the spectral-bathymetrymodels will also integrate with Particle Swarm Optimization (PSO) to increase the reliability of thederived bathymetric results.
|Effective start/end date||1/08/18 → 31/07/19|
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
- bathymetric mapping
- linear and nonlinear spectral modeling
- Particle SwarmOptimization
- high-resolution multi-spectral satellite images
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