DuckDB 空间数据管理指南
从 SQL 基础到高级地理空间分析
释放 DuckDB 在现代地理空间分析中的强大能力。本书通过实践导向的方式，帮助 GIS 专业人员掌握高效的空间数据管理方法，利用 SQL、Python 以及 DuckDB 的空间扩展，将海量真实世界数据转化为有价值的洞察。全彩印刷版可在 Amazon 上购买。
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About the Book
使用 DuckDB 掌握现代空间数据管理。DuckDB 是一款快速而高效的分析型数据库，正在重塑 GIS 专业人员处理地理空间数据的方式。本书从基础 SQL 概念出发，逐步深入到高级地理空间分析，通过真实世界数据集的动手示例，帮助你建立扎实而实用的能力。这些数据集包括美国国家湿地数据集、Overture 全球建筑轮廓数据，以及纽约市出租车数据。
你将深入了解 DuckDB 的空间扩展以及与 GDAL 的集成方式，从而以前所未有的速度和效率处理海量地理空间数据。通过 14 个实践性章节，配合可直接运行的代码示例和循序渐进的教程，你将学会处理 Shapefile、GeoJSON、GeoParquet 以及 PMTiles 等云原生格式，并构建交互式地图和仪表板，让数据真正“活”起来。
本书适合谁
本书面向希望在地理空间工作流程中使用 DuckDB 的 GIS 分析师、数据科学家和空间开发者。无论你是从传统 GIS 工具转型，还是希望更高效地处理大规模数据，亦或是希望将空间分析集成到现代数据流水线中，本书都能为你提供实用指导。具备基本的空间概念将有所帮助，但不要求事先具备 DuckDB 或 SQL 经验。
你将掌握的技能
- 安装和配置带有空间扩展的 DuckDB
- 编写并优化用于空间数据操作的 SQL 查询
- 将 DuckDB 与 Python、Pandas 和 Polars 集成
- 导入和导出地理空间格式，包括 Shapefile、GeoJSON、GeoParquet 和 PMTiles
- 执行几何运算、投影和测量
- 运行空间连接、点在多边形内分析和最近邻查询
- 使用 Leafmap 和 Jupyter Notebook 进行交互式可视化
- 使用 PMTiles 和矢量瓦片可视化大规模云原生数据
- 基于湿地、建筑和出行数据的案例研究
- 使用 Solara 构建动态仪表板
- 针对大规模地理空间处理进行性能优化
- 利用 GDAL 实现高级格式支持和数据转换
主要特色
- 以实践为导向，所有示例代码均可直接运行
- 每章配有练习，帮助巩固所学内容
- 全书贯穿真实世界数据集和案例
- 与 Python 生态系统无缝集成，包括 Leafmap、Pandas 和 GeoPandas
- 全面覆盖 DuckDB 1.4.x 的空间功能
- 清晰、循序渐进的生产级分析工作流程
- 专家级故障排查建议和性能调优经验
在本书结束时，你将能够自信地使用 DuckDB 进行空间数据管理和分析，轻松处理任意规模的数据集，完成复杂的空间分析，并构建高性能、交互式应用，挖掘深层次的地理空间洞见。
Author
About the Author
Dr. Qiusheng Wu is an Associate Professor at the University of Tennessee and an Amazon Scholar. His research focuses on geospatial data science, with an emphasis on using open-source Python tools and cloud computing to study environmental change. He is the creator of several widely-used Python packages, including geemap, leafmap, and geoai, and is dedicated to advancing geospatial analysis and visualization. Dr. Wu's work is a cornerstone of the open-source geospatial community, and he brings his deep expertise to this book, guiding you through the process of learning and mastering geospatial programming with Python.
Episode 318
An Interview with Qiusheng Wu
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