GeoAI

GeoAI is a comprehensive Python package designed to bridge artificial intelligence (AI) and geospatial data analysis. It provides researchers and practitioners with intuitive tools for applying machine learning techniques to geographic data. The package offers a unified framework for processing satellite imagery, aerial photographs, and vector data using state-of-the-art deep learning models, integrating popular AI frameworks and specialized geospatial libraries. This enables users to perform complex geospatial analyses with minimal code.

The package provides five core capabilities. These include interactive and programmatic search and download of remote sensing imagery and geospatial data, along with automated dataset preparation that involves image chips and label generation. GeoAI supports model training for tasks such as classification, detection, and segmentation. It also offers inference pipelines for applying models to new geospatial datasets and interactive visualization through integration with tools like Folium and ipyleaflet.

GeoAI addresses the growing demand for accessible AI tools in geospatial research by providing high-level APIs that abstract complex machine learning workflows. The package supports multiple data formats including GeoTIFF, JPEG2000, GeoJSON, Shapefile, and GeoPackage, and includes automatic device management for GPU acceleration. With extensive Jupyter notebook examples, GeoAI serves as both a research tool and an educational resource for the geospatial AI community, facilitating applications in areas like environmental monitoring, urban planning, disaster response, and climate research.