Services / Multispectral, SAR, time-series monitoring
Satellite Analytics & Change Detection
We process multispectral and radar imagery into monitoring products that work through cloud cover and at scale. Sentinel-1 SAR fused with Sentinel-2 optical resolves soil moisture from 0.05 to 0.45 m³/m³. Google Earth Engine carries the pipelines from a single field to a continent.
Capabilities
What the work involves
SAR processing and fusion
Sentinel-1 backscatter fused with optical indices using the Water Cloud Model to remove vegetation effects and recover surface moisture.
Time-series change detection
Historical backscatter and index anomalies flag irrigation events, drought onset, and land-use change as they happen.
Wildfire and climate impact assessment
Burn severity, drought patterns, and ecosystem change mapped with published methods.
Cloud and shadow screening
Automated quality masking at over 90% detection accuracy keeps time series clean.
Tooling
- Google Earth Engine
- Sentinel-1 SAR
- Sentinel-2
- Landsat
- Planet
- Python
Deliverables
What you receive
- Analysis-ready raster and vector products
- Operational GEE monitoring pipelines, handed over with documentation
- Time-series dashboards and alert thresholds
- Methods report suitable for regulatory or funding review
Where it applies
Markets served by this service
Delivered work
This service in the field
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