Seeing India's air from space. AI-powered satellite intelligence that maps surface Air Quality and HCHO hotspots across the nation - even where no monitor exists.
CPCB's monitoring network covers only ~500 stations - mostly in urban centres. The vast majority of India's 1.4 billion people live beyond the reach of any ground monitor.
Average distance to the nearest air quality monitor for rural India
Our solution: Use INSAT-3D, TROPOMI, and a CNN-LSTM model to convert satellite column readings into daily surface-level AQI maps - covering every square kilometre of India.
Our pipeline transforms raw satellite columns into actionable, daily surface AQI maps and HCHO hotspot intelligence.
INSAT-3D AOD, TROPOMI NO₂/SO₂/CO/O₃/HCHO, CPCB ground truth, IMDAA/ERA5 meteorology, FIRMS fire data
Google Earth Engine harmonization, regridding, quality control, cloud masking, temporal alignment
Columns + PBLH + humidity + ventilation coefficient + wind + solar zenith + aerosol layer height + temporal features
Hybrid deep learning: CNN captures spatial patterns, LSTM captures temporal dependencies. Predicts surface concentrations from satellite features.
Compare predictions against CPCB ground truth. Evaluate with RMSE, R², and MAE. Station-level and spatial cross-validation.
Daily surface AQI maps, HCHO hotspot detection via DBSCAN, source-region identification, fire transport analysis with HYSPLIT.
Most teams map AOD straight to PM2.5. We add the physics that turns a column reading into a real ground-level value.
PBLH controls how deep pollutants mix. Shallow winter boundary layers trap pollution near the surface - this is the #1 predictor most models miss.
Humidity swells aerosol particles, inflating AOD relative to dry PM mass. Without RH correction, the column→surface mapping breaks down.
PBLH × wind speed - a confirmed strong PM2.5 predictor over the Indo-Gangetic Plain. Combines vertical mixing with horizontal dispersion.
Solar radiation drives O₃ and HCHO formation. The HCHO/NO₂ ratio indicates VOC- vs NOx-limited ozone regimes - key for Objective 2.
Generate daily, gap-free spatial maps of surface Air Quality Index covering all of India. Every CPCB pollutant folds into a single AQI value.
Map spatio-temporal HCHO hotspots during biomass-burning seasons, identify source regions, and track fire-driven transport.
India-first, open-source, satellite-powered.