Water quality monitoring
Multispectral indicators of turbidity, chlorophyll-a, and algal blooms across entire river stretches and lakes — wall-to-wall context that sparse ground sensors cannot provide.
- Whole-river coverage
- Bloom & hotspot flags
- Complements ground sensors
Benefits
What water quality monitoring unlocks
Short-term optimization
- Locate pollution hotspots along hundreds of kilometres of river
- Detect algal blooms in lakes and reservoirs early
- Prioritise where ground sampling teams should go
Long-term impact
- Seasonal and multi-year water-quality baselines
- Programme-level evidence for river-rejuvenation missions
- Encroachment and discharge patterns near water bodies
Approach & methodology
How the analytics work
We are transparent about data sources, models, and limits — so you can trust what you act on.
- Data sources
- 10 m multispectral optical imagery with water-quality spectral indices; historical archives for baselines.
- Approach
- Index-based retrieval of turbidity and chlorophyll-a, calibrated against available in-situ measurements; anomaly detection for hotspots.
- Update cadence
- Each clear-sky pass; weekly composites in monsoon-affected periods.
- Limitations
- Optical retrievals are surface indicators, not lab assays; cloud and sun-glint reduce usable observations.
Deliverables
Expected outputs
- GIS-ready data layers (GeoJSON / KML / SHP / GeoTIFF)
- Decision-ready PDF report with interpretation
- Interactive smart map with time-series view
Process
Project stages
2–4 weeks to first river-stretch assessment
Define area of interest and indicators with your team
Acquire and process multi-date satellite imagery
Run analytics models and validate outputs
Deliver layers, maps, and report; set up recurring monitoring