{"name": "SDB Production Suite", "package_name": "sdb_production_suite", "description": "Professional Satellite Derived Bathymetry (SDB) generation tool using Random Forest Regression.", "about": "This suite provides high-precision bathymetric mapping tools for the 2026 Apurawan/Ilian project. It integrates ACOLITE-processed multispectral data with surveyed sonar points to create MLLW-referenced seafloor models. Supported by Gemini AI Adaptive Architecture.", "homepage": "https://github.com/AlvinMN2024/SDB_Suite", "repository": "https://github.com/AlvinMN2024/SDB_Suite", "tracker": "https://github.com/AlvinMN2024/SDB_Suite/issues", "author": "Alvin M. Natividad", "tags": ["remote sensing", "hydrography", "machine learning", "bathymetry", "sentinel-2"], "downloads": 197, "latest_version": "1.0.1", "versions": [{"version": "1.0.1", "experimental": false, "qgis_min": "4.0.0", "qgis_max": "4.99.0", "downloads": 197, "uploaded_by": "alvinmn", "upload_datetime": "2026-04-01T02:13:14.209850"}]}