Welcome! This repository is your gateway to the essential resources, trends, and tools shaping the GeoAI landscape with Python.
Watch the video overview:
Click the image above or watch on YouTube.
This report series was inspired by the concept of a "vibe-coding" GeoAI assistant—analyzing and curating the core Python libraries, methodologies, and data platforms that power modern geospatial AI workflows. The goal: help professionals and enthusiasts automate complex geospatial tasks (data acquisition, processing, ML/AI integration) with intuitive, high-level tools.
GeoAI, driven by Python, is rapidly evolving. This research is designed to keep you ahead of the curve—whether you work in GIS, remote sensing, data science, or related fields.
- Core Python Libraries: e.g.,
GeoPandas,Rasterio,Scikit-learn, and more - Key GeoAI Workflow Patterns & Automation: e.g., using STAC, COG
- Top Open Data Platforms: e.g., Planetary Computer, Google Earth Engine
- Future Outlook: Foundation Models, XAI, and more
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📄 Full Interactive Report: GeoAI_Python_Resources_v1.0.html
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📊 Visual Infographic: GeoAI_Python_InfoGraphic_v1.0.html
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🎧 Audio Overview: GeoAI_Python_Resources_v1.0.mp3
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🎬 Video Overview:
Click the image above or watch on YouTube.
Your feedback and thoughts are welcome as we continue to explore this exciting field. Feel free to open an issue or connect!
GeoAI · PythonForGIS · ArtificialIntelligence · DataScience · Geospatial · OpenSource · TechTrends · MachineLearning · VibeCoding · RemoteSensing