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GeoAI Development with Python: Designing Intelligent Geospatial Models for Prediction, Analysis, and Spatial Insights
GeoAI Development with Python explores the intersection of geospatial technology and artificial intelligence, providing a comprehensive guide to building intelligent spatial systems.
This book focuses on applying machine learning and deep learning techniques to geospatial data. You will learn how to prepare spatial datasets for AI models, engineer features from geographic information, and develop predictive systems that uncover patterns across space and time.
Through practical examples, the book covers topics such as spatial machine learning workflows, computer vision for satellite imagery, geospatial data pipelines, and model deployment. It also introduces techniques for handling real-world challenges like data imbalance, spatial correlation, and scalability.
Designed for developers with a basic understanding of Python and GIS, this book bridges the gap between traditional geospatial analysis and modern AI-driven solutions. By the end, you will be equipped to build intelligent applications that transform raw geographic data into actionable insights.
This book focuses on applying machine learning and deep learning techniques to geospatial data. You will learn how to prepare spatial datasets for AI models, engineer features from geographic information, and develop predictive systems that uncover patterns across space and time.
Through practical examples, the book covers topics such as spatial machine learning workflows, computer vision for satellite imagery, geospatial data pipelines, and model deployment. It also introduces techniques for handling real-world challenges like data imbalance, spatial correlation, and scalability.
Designed for developers with a basic understanding of Python and GIS, this book bridges the gap between traditional geospatial analysis and modern AI-driven solutions. By the end, you will be equipped to build intelligent applications that transform raw geographic data into actionable insights.
205 pages, Kindle Edition
Published April 3, 2026
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