Using GitHub as a Wildfire Time-Series Database: A Geospatial Aviation Pipeline
📰 Hackernoon
Learn how to build a geospatial aviation pipeline using GitHub as a time-series database to correlate wildfire incident data with live aircraft positions, and why this approach is effective
Action Steps
- Build a data pipeline using GitHub as a time-series database
- Configure data ingestion from InciWeb and FlightAware APIs
- Apply the Haversine formula for geospatial matching
- Run data analysis on the correlated dataset
- Test the pipeline for data consistency and accuracy
- Visualize the results using a mapping library
Who Needs to Know This
Data engineers, data scientists, and software engineers on a team can benefit from this approach to build a scalable and efficient pipeline for geospatial data analysis, and to inform decision-making in wildfire management and aviation
Key Insight
💡 GitHub can be used as a time-series database for geospatial data, enabling efficient and scalable data analysis
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🚁💻 Using GitHub as a time-series database for geospatial aviation data 🚁💻
Key Takeaways
Learn how to build a geospatial aviation pipeline using GitHub as a time-series database to correlate wildfire incident data with live aircraft positions, and why this approach is effective
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