Welcome to the Ciampitti Lab GitHub!
We are a research group pushing the frontiers of crop physiology, digital agriculture, and data-driven farming systems. Our mission is to integrate new technologies and data science to improve the prediction and management of farming systems for the benefit of growers worldwide.
🌾 Cropping Systems • 🖥️ Crop Modeling
🎓 Extension • 🛰️ Remote Sensing & Digital Farming
A bibliometric analysis script that fetches and analyzes academic publication data
Next.js source & content for the Ciampitti Lab website (code MIT, content CC BY‑4.0)
Field-scale winter-wheat phenology across the U.S. HRW belt: physiology-informed (WES) with machine learning.
Wheat grain protein concentration prediction using Sentinel-2 time series, meteorological data, and machine learning
Interactive 3D visualization of agricultural land use and seasonal vegetation dynamics across the U.S. Corn Belt. Integrates USDA CDL, SRTM terrain, and Sentinel-2 imagery in a browser-based WebGL environment.
A study comparing: segmentation models on different crops, genotypes and vegetative development
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