HomeAI & Machine LearningHyperspectral Crop Disease Detector

Hyperspectral Crop Disease Detector

Interactive 3D canopy simulator: an infection spreads through a leaf grid while a hyperspectral Spectral Angle Mapper classifier scans reflectance signatures and flags disease before it is visible to the eye.

AI & Machine Learning3DModerate60 FPS📱 Mobile-adapted⇄ 2D version
ai-topic-59 ↗ Open standalone

A 100-leaf canopy grid renders as an instanced 3D field while a simulated infection — fungal blight or viral mosaic — spreads outward from a patient-zero leaf by logistic growth and diffusion to its neighbours. Every leaf carries its own synthetic 8-band reflectance spectrum (450–860 nm) that drifts from the healthy reference curve as infection progresses, mirroring real red-edge and near-infrared stress signatures used in agricultural remote sensing. Click any leaf, or run "Scan all leaves", to classify it with a genuine hyperspectral algorithm — the Spectral Angle Mapper — which measures the angle between the leaf's measured spectrum and reference curves for healthy, fungal and viral tissue. Because the spectral drift begins well before a human eye can see discoloration, the AI regularly flags leaves as infected while they still look green, and the live scoreboard tracks exactly how many of those pre-symptomatic catches it makes against the count a visual scout would see.

⚙ Under the hood

A logistic-growth infection spreads across a 3D canopy of 100 leaves while a real Spectral Angle Mapper classifier scans each leaf's simulated 8-band reflectance spectrum, flagging fungal blight or viral mosaic before symptoms are visible to the eye.

AIagriculturehyperspectralplant diseaseremote sensingprecision farming

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install

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