[{"_1":2,"_46":-5,"_47":-5},"loaderData",{"_3":4,"_14":15,"_44":-5,"_45":-5},"root",{"_5":-5,"_6":-5,"_7":-5,"_8":9,"_10":11},"user","shoppingCartId","toast","locale","en","constants",{"_12":13},"paypalClientId","AenrHU49peF-ZUH-Yq7AXLLNZYGUGlml474U16NCjB4ZznmQCEjiliN3whyuVZmkb7VxEzmTALgtKEKE","routes/_store+/_readers+/email_author.$slug/route",{"_16":17,"_43":-5},"book",{"_18":19,"_20":21,"_22":23,"_24":25,"_26":27,"_28":29},"id","Z2lkOi8vbGVhbnB1Yi9TdG9yZTo6Qm9va1Byb2R1Y3QvNjgxMTY","title","Spatial Data Management with DuckDB","state","published","contactAuthorMethod","email","aboutText","

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
Visualize large-scale cloud-native datasets using PMTiles and vector tiles
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.

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