Home▸AI & Machine Learning▸Satellite AI Emission Tracker — 2D Column View

Satellite AI Emission Tracker — 2D Column View

A 2D top-down satellite column-density view of a Gaussian-plume dispersion model: an AI mass-balance algorithm integrates noisy downwind column readings to estimate the true emission rate, exactly as GHGSat, Sentinel-5P and MethaneSAT retrieval pipelines do. Drag to pan, scroll to zoom.

AI & Machine Learning2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

Details

CategoryAI & Machine Learning

RenderingCanvas 2D

DifficultyModerate

Target FPS60

ControlsSliders for true emission rate Q, wind speed, sensor noise and detection threshold; a dropdown for Pasquill-Gifford atmospheric stability class (A-F); a Resample button that draws a fresh noise realisation; a Reset view button. Drag the canvas to pan and scroll/wheel to zoom the satellite column-density map.

satellite-monitoringgaussian-plumemethane-emissionsmass-balanceai-retrievalatmospheric-dispersionremote-sensing

Related simulations

Gradient Descent VisualiserWatch SGD, Momentum, RMSprop and Adam navigate a 3D loss landscape in real time. Compare…

K-Means Clustering — Machine Learning VisualiserVoronoi regions and centroid trails update as K-Means++ steps through blob, half-moon or…

Convolutional Neural NetworkA filter scans an 8×8 image layer by layer — watch convolution, ReLU activation and… ⊞ All 1171 in AI & Machine Learning →

This simulator renders a real Gaussian atmospheric-dispersion plume, viewed the way a satellite instrument actually sees it: a top-down map of column density drifting downwind from a facility stack. It then runs the same mass-balance retrieval that AI-assisted satellite missions (GHGSat, Sentinel-5P TROPOMI, MethaneSAT) use to turn a noisy image of a gas plume into an estimated emission rate — without ever measuring the source directly. Adjust the true emission rate, wind speed and atmospheric stability class to reshape the physical plume, then tune the sensor noise and the AI classifier's detection threshold to see how instrument noise and threshold clipping bias the recovered estimate away from the ground truth. Drag the canvas to pan and scroll to zoom into the plume.

⚙ Under the hood

A top-down 2D satellite view of a Gaussian methane/CO2 plume drifting downwind from a facility stack: an AI mass-balance algorithm integrates noisy column-density readings along a downwind line to estimate the true emission rate, exactly as GHGSat, Sentinel-5P and MethaneSAT retrieval pipelines do. Adjust the emission rate, wind, stability, sensor noise and detection threshold, then drag to pan and scroll to zoom across the plume.

satellite-monitoringgaussian-plumemethane-emissionsmass-balanceai-retrievalatmospheric-dispersionremote-sensing

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install