satellite_derived_bathymetry_for_qgis
A comprehensive and automated toolkit for Satellite-Derived Bathymetry (SDB) using machine learning, featuring integrated ICESat-2 data retrieval.
This plugin is deprecated and no longer maintained. Please use "Bathymetrix-AI" instead
---- This Plugin is deprecated not supported anymore. you can try "Bathymetrix-AI".----
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 scientific research and hydrography, following IHO recommendations.
New Feature: ICESat-2 Integration
The toolkit now includes a dedicated module to download and filter ICESat-2 photon data (ATL03/ATL24) via the SlideRule API. This allows users to easily obtain high-precision bathymetry control points for model training and validation.
Workflow Stages:
1-Data Retrieval: Automated download of ICESat-2 bathymetry (SlideRule).
2-Pre-processing: Smart water masking (MNDWI/NDWI) and morphological cleaning.
3-Model Training: Algorithm comparison with hyperparameter tuning (Bayesian Optimization).
4-Refinement: Optional median filtering to reduce noise.
5-Evaluation: Statistical scoring (70% R², 30% RMSE) and reporting.
References:
IHO Publication B-13: Cookbook for Satellite-Derived Bathymetry (IHO website).
Stumpf et al. (2003): Band Ratio Model in Limnology and Oceanography.
SlideRule Earth: Processing of ICESat-2 data (slideruleearth.io).
Acknowledgements:
Development leveraged AI-assisted tools: Google Gemini Pro & OpenAI ChatGPT for workflow optimization and SlideRule integration.