Spatial Data Management with DuckDB
Spatial Data Management with DuckDB
From SQL Basics to Advanced Geospatial Analytics
About the Book
Master modern spatial data management with DuckDB, the fast and efficient analytical database that's transforming how GIS professionals work with geospatial data. This comprehensive guide takes you from fundamental SQL concepts to advanced geospatial analytics, with hands-on examples using real-world datasets including the US National Wetlands Inventory, Overture global building footprints, and NYC taxi data.
Discover how DuckDB's spatial extension and GDAL integration enable you to process massive geospatial datasets with unprecedented speed and efficiency. Through 14 practical chapters filled with working code examples and step-by-step tutorials, you'll learn to handle Shapefiles, GeoJSON, GeoParquet, and cloud-native formats like PMTiles, while building interactive maps and dashboards that bring your data to life.
Who This Book Is For:
This book is designed for GIS analysts, data scientists, and spatial developers who want to leverage DuckDB for their geospatial workflows. Whether you're transitioning from traditional GIS tools, looking to handle larger datasets more efficiently, or seeking to integrate spatial analysis into modern data pipelines, this book provides the practical guidance you need. A basic understanding of spatial concepts is helpful, but no prior DuckDB or SQL experience is required.
What You Will Learn:
- Install and configure DuckDB with the spatial extension
- Write and optimize SQL queries for spatial data operations
- Integrate DuckDB with Python, Pandas, and Polars
- Import and export geospatial formats: Shapefile, GeoJSON, GeoParquet, PMTiles
- Perform geometry operations, projections, and measurements
- Run spatial joins, point-in-polygon, and nearest-neighbor queries
- Visualize data interactively using Leafmap and Jupyter Notebooks
- Analyze large-scale cloud-native datasets using PMTiles
- Work with case studies on wetlands, buildings, and mobility data
- Build dynamic dashboards with Solara
- Optimize performance for large-scale geospatial processing
- Leverage GDAL for advanced format support and conversions
Key Features:
- Hands-on, example-driven approach with fully working code
- Chapter-end exercises to reinforce learning
- Real-world datasets and case studies throughout
- Seamless Python ecosystem integration (Leafmap, Pandas, GeoPandas)
- Comprehensive coverage of DuckDB 1.4.x spatial features
- Clear, step-by-step workflows for production-ready analytics
- Expert troubleshooting tips and performance tuning insights
By the end of this book, you'll be able to confidently use DuckDB for your spatial data management and analysis workflows, processing datasets of any size, performing complex spatial analysis with ease, and building interactive, high-performance applications that reveal deep geospatial insights.
About the Author
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