{"name": "Bathymetrix-AI", "package_name": "Bathymetrix_AI", "description": "An advanced Machine Learning pipeline for Satellite-Derived Bathymetry (SDB). Features ICESat-2 integration, In-Situ Data filtering, and Spatial Residual Stacking.", "about": "Bathymetrix-AI is a specialized QGIS research toolkit designed to derive high-precision bathymetry from corrected multispectral satellite imagery (e.g., Sentinel-2 L2A). It systematically integrates physics-based corrections with data-driven Machine Learning to overcome traditional SDB limitations.\r\n\r\nCore Workflow (The 4-Phase System):\r\n\r\n1. Automated Pre-processing: Sun-glint removal (Hedley), new Advanced Water Masking (3-Indices), physics-based feature generation (Log-Ratios), and a Deep Water Filter fully customized for ML algorithms.\r\n\r\n2. Robust Altimetry Filtering: Uses different algorithms to clean ICESat-2 (ATL24) data by identifying high-confidence inliers and removing environmental noise.\r\n\r\n3. Global Auto-ML Modeling: Competitive benchmarking of 11 ML algorithms with Randomized Hyperparameter Optimization to find the optimal global depth function.\r\n\r\n4. Spatial Residual Stacking: Enhances accuracy by analyzing prediction residuals and re-training the model with a Stacked Error Surface to correct local biases.\r\n\r\nKey References:\r\n\r\nStumpf et al. (2003): Log-Ratio Algorithm for SDB inversion.\r\n\r\nHedley et al. (2005): Physics-based sun-glint correction.\r\n\r\nFischler & Bolles (1981): RANSAC algorithm for ICESat-2 data filtering.\r\n\r\nZhang et al., (2021): LS Variance Fit, or Huber Variance Fit for ICESat-2 data filtering.\r\n\r\nAlevizos (2020): Residual analysis and spatial refinement in shallow waters.\r\n\r\nBergstra & Bengio (2012): Randomized search for hyperparameter optimization.\r\n\r\nParrish et al. (2025): Analysis and assessment of global ICESat-2 bathymetry.\r\n\r\nDeveloped for scientific research and hydrographic applications. Creating the Codes and documentation optimized using Google Gemini AI.", "homepage": "https://github.com/Nasef2017/Bathymetrix-AI", "repository": "https://github.com/Nasef2017/Bathymetrix-AI", "tracker": "https://github.com/Nasef2017/Bathymetrix-AI/issues", "author": "Mohamed Aly Nasef", "tags": ["python", "remote sensing", "hydrography", "machine learning", "bathymetry", "sentinel-2", "sdb", "icesat-2", "spatial correction", "ransac"], "downloads": 3088, "latest_version": "5.0", "versions": [{"version": "5.0", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "4.99.0", "downloads": 58, "uploaded_by": "nasefmaly", "upload_datetime": "2026-06-21T03:44:36.916673"}, {"version": "4.8", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "4.99.0", "downloads": 376, "uploaded_by": "nasefmaly", "upload_datetime": "2026-05-25T17:49:03.248788"}, {"version": "4.7", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "4.99.0", "downloads": 291, "uploaded_by": "nasefmaly", "upload_datetime": "2026-05-09T06:24:06.990974"}, {"version": "4.6", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 241, "uploaded_by": "nasefmaly", "upload_datetime": "2026-04-23T07:20:30.150107"}, {"version": "4.5", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 98, "uploaded_by": "nasefmaly", "upload_datetime": "2026-04-22T04:58:17.735258"}, {"version": "4.4", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 70, "uploaded_by": "nasefmaly", "upload_datetime": "2026-04-22T03:00:50.708322"}, {"version": "4.3", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 253, "uploaded_by": "nasefmaly", "upload_datetime": "2026-04-07T00:01:56.962288"}, {"version": "4.2", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 84, "uploaded_by": "nasefmaly", "upload_datetime": "2026-04-02T13:40:52.819255"}, {"version": "4.1", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 552, "uploaded_by": "nasefmaly", "upload_datetime": "2026-02-22T01:51:22.218820"}, {"version": "4.0", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 416, "uploaded_by": "nasefmaly", "upload_datetime": "2026-01-29T12:50:52.978416"}, {"version": "3.3", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 159, "uploaded_by": "nasefmaly", "upload_datetime": "2026-01-25T13:22:28.905958"}, {"version": "3.2", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 196, "uploaded_by": "nasefmaly", "upload_datetime": "2026-01-11T23:41:05.860406"}, {"version": "3.1", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 89, "uploaded_by": "nasefmaly", "upload_datetime": "2026-01-10T23:43:49.931487"}, {"version": "3.0", "experimental": false, "qgis_min": "3.22.0", "qgis_max": "3.99.0", "downloads": 204, "uploaded_by": "nasefmaly", "upload_datetime": "2025-12-30T09:52:02.168442"}]}