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- Created parallel spatial_data module following ETL pipeline plan v3 - Implemented MNGeospatialExtractor for MN Geospatial Commons datasets - Added CLI integration with spatial-data command - Set up dataset registry with protected_areas test dataset - Follows software engineering best practices with clean separation from sensor data Phase 1 MVP: Basic structure and MN Geospatial extractor Next: Install dependencies and test actual data extraction 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
- Documents current Phase 1 MVP implementation status - Explains extractors vs parsers architecture decision - Provides usage examples and CLI command reference - Outlines testing roadmap and development priorities - References related design documents and technical analysis Module now has complete documentation for early-stage development 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
- TESTED: MN Geospatial Commons data extraction (1,731 features successfully extracted) - Fixed CLI decorator usage for proper Click integration - Resolved Unicode encoding issues for Windows compatibility - Updated README with comprehensive testing results and status - Validated complete ETL pipeline: download → extract → process → validate - Performance confirmed: 0.8s extraction time for 1,731 MultiPolygon features - CRS transformation working: EPSG:26915 → EPSG:4326 Ready for Phase 2: File export capabilities 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
… integration - Implement GeoParquet file export with compression and metadata - Add PostGIS database schema for spatial data catalog and logging - Create spatial data logger with extraction tracking - Update CLI commands with file output support and improved UX - Add support for multiple output formats (GeoParquet, Shapefile, CSV) - Integrate raster processing with rasterio dependency - Test end-to-end pipeline with both vector and raster datasets - Update documentation with production-ready status and usage examples Verified extraction performance: - Vector data: 1,731 features in 0.8s (2.9 MB GeoParquet) - Raster data: 201,264 features in 14.5s (5.6 MB GeoParquet) 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
- Update status to 'Prototype Complete' for accuracy - Add documentation files for GeoParquet decision matrix and architecture - Improve formatting in Technical Decisions section 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
- Format all Python files to comply with Black code style - No functional changes, only formatting updates 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
- Sort imports with isort to comply with project standards - No functional changes, only import order updates 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
zradlicz
approved these changes
Jan 8, 2026
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Summary
spatial_datamodule with extractor architecture for spatial datasetsKey Features
list-datasets,test,extractwith flexible output optionsProduction Validation
Architecture
Files Added
extractor.py, base classes, registry systemTest Plan
🤖 Generated with Claude Code