AI agent for geospatial analysis with Sentinel-2 satellite imagery
Project description
An Geospatial AI-Agent for analysis with satellite imagery.
Type a plain-English query - GeoMind handles everything else.
GeoMind lets you interact with satellite data through natural language. No code, no GIS software, no manual downloads. Describe what you want - GeoMind geocodes the location, searches the satellite archive, streams only the data it needs, and saves the result to your machine in seconds.
It can generate RGB true-color composites, calculate NDVI vegetation indices, apply cloud cover filters, retrieve band statistics, and handle multiple products in a single query. Queries can reference place names, cities, regions, or raw coordinates. A single instruction like "get a recent image of Scotland and its NDVI" will trigger search, composite generation, and vegetation analysis automatically.
How It Works
Your query -> Geocoding -> Catalog search -> Stream band data -> Image output
"Paris RGB" Paris coords Recent scenes ~1-5 MB via Zarr outputs/*.png
- Geocoding - place name is converted to coordinates and a bounding box
- Catalog search - recent Sentinel-2 L2A scenes retrieved from STAC API
- Cloud-native streaming - only the required band chunks are downloaded (~1–5 MB instead of ~720 MB full scene)
- Processing - bands are scaled, stacked, and rendered as PNG
- Output - image saved to
outputs/and opened automatically
Traditional vs GeoMind
Traditional: Full Scene Download -> Local Storage -> Process -> Result
~720 MB Disk I/O Slow
GeoMind: HTTP Range Request -> Stream Chunks -> Process -> Result
~1-5 MB No disk Fast
Installation
pip install geomind-ai
Quick Start
1. Get a free API key at openrouter.ai/settings/keys
2. Launch GeoMind:
geomind
3. Enter your key on first run (saved automatically - never asked again):
OpenRouter API key required (FREE)
Get yours at: https://openrouter.ai/settings/keys
Enter your API key: sk-or-v1-xxxxxxxxxxxxxxxxxxxxxxxx
API key saved!
4. Start querying:
> get me a recent image of scotland and its ndvi
Executing: list_recent_imagery({'location_name': 'Scotland'})
Executing: create_rgb_composite({...})
Executing: calculate_ndvi({...})
RGB composite: outputs/rgb_composite_7066.png
NDVI: outputs/ndvi_9664.png
NDVI stats: min -0.72 / max 0.91 / mean 0.34
Single Query Mode
geomind --query "Find recent imagery of Paris with less than 10% cloud cover"
Requirements
- Python 3.10+
- Free OpenRouter API key
Documentation
Full documentation at harshshinde0.github.io/GeoMind
Project details
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