Proprietary applied research
BGPD Agricultural Intelligence Engine
A geospatial decision-system foundation for identifying persistent relative vegetation behavior before intensive field investigation.
The challenge
Agricultural variability is difficult to understand when field surveys, soil sampling or farm-level history are not yet available. BGPD explores how multitemporal Earth Observation can provide an initial spatial hypothesis of where behavior differs consistently over time.
- Sector: agriculture and land-based operations
- Classification: proprietary applied research and geospatial decision-system foundation
Workflow
The system is designed as an operational workflow from Area of Interest intake through standardized outputs and reporting.
- Area of Interest
- Historical Sentinel-2 imagery
- Vegetation signals
- Temporal normalization
- Spatial pattern analysis
- Unsupervised clustering
- Relative behavior zones
- Maps, statistics and decision support
What the zones mean
The zones represent relative persistent vegetation behavior in the analyzed observations. They do not establish absolute fertility, yield, crop health or an agronomic diagnosis. Their purpose is to help prioritize inspection, sampling, anomaly review and further investigation.
- Satellite-derived hypotheses remain distinct from field measurements
- Results can be extended with soil, terrain, weather, crop history, yield and field observations
- Professional agronomic interpretation remains necessary
Capabilities demonstrated
Multitemporal Sentinel-2 processing, AOI validation, raster analysis, temporal normalization, clustering, spatial statistics, standardized reporting and automated delivery workflows.