Tired of manual GIS processes? Elevate your skills and career with Python-powered geospatial automation.
GIS Programming in Practice is designed for ambitious GIS professionals, data scientists, and Python developers who want to tackle large-scale spatial challenges. This comprehensive guide empowers you to build scalable, efficient, and robust solutions for analyzing and visualizing spatial data.
Move beyond basic scripting and learn to integrate your Python GIS projects with powerful databases and cloud platforms. Discover strategies for handling large geospatial datasets and optimizing performance, making your applications ready for real-world demands.
Key Features:
Advanced Automation: Implement sophisticated scripts for complex GIS workflows and data pipelines.
Database Integration: Master storing and querying spatial data with PostGIS and connecting via Python (Psycopg2, SQLAlchemy).
Cloud GIS: Understand how to leverage AWS, Google Cloud, and Azure for scalable geospatial processing and storage.
Performance Optimization: Learn techniques like chunking, parallel processing, and spatial indexing for faster queries and efficient memory management.
Geospatial Machine Learning: A practical introduction to spatial regression, clustering, and feature engineering for predictive mapping.
Professional Development: Adopt essential practices like debugging, unit testing, and version control with Git for collaborative projects.
Become the go-to expert for geospatial development in your organization. This book provides the deep knowledge and practical examples you need to build cutting-edge open-source GIS solutions.
By Jaxon Myles