satellite_derived_bathymetry_for_qgis
Plugin ID: 4223
A comprehensive and automated toolkit for Satellite-Derived Bathymetry (SDB) using machine learning.
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SDB Master Workflow
The SDB Master Workflow is a powerful QGIS tool that automates Satellite-Derived Bathymetry (SDB) processing. It combines preprocessing, algorithm testing, objective ranking of models, and automated reporting. The tool is designed for both scientific research and practical applications in hydrography and coastal engineering. It follows international recommendations (IHO) and supports reproducible and efficient workflows.
Workflow Stages:
1. Pre-processing and smart water masking (MNDWI/NDWI + morphological cleaning).
2. Algorithm comparison with hyperparameter tuning (Bayesian Optimization).
3. Optional median filtering to reduce noise.
4. Evaluation using test points with weighted scoring (70% R², 30% RMSE).
References:
- IHO Publication B-13: Cookbook for Satellite-Derived Bathymetry (IHO website)
- Stumpf et al. (2003). Band Ratio Model in Limnology and Oceanography.
- Caballero & Stumpf (2019). Machine Learning vs Band Ratio in Remote Sensing.
Acknowledgements:
Development and refinement of this plugin leveraged AI-assisted tools: Google Gemini Pro (workflow design, debugging, optimization), OpenAI ChatGPT (initial scaffolding, troubleshooting).
