Services / Multispectral, SAR, time-series monitoring
Satellite Analytics & Change Detection
We turn multispectral and radar imagery into monitoring products that hold up regardless of clouds, smoke, or haze. Sentinel-1 SAR fused with Sentinel-2 optical shows what changed, when, and by how much, early enough to act on. Built on Google Earth Engine, so the analysis scales from a single parcel to an entire region.
Applications include, but are not limited to, vegetation encroachment, wildfire burn severity, structure survival assessment, flood inundation, water stress and irrigation scheduling, crop yield and biomass forecasting, forest carbon stock, and land cover change.
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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