Agricultural Intelligence Engine
Relative persistent vegetation behavior from multitemporal Sentinel-2 observations.
Learn more: Agricultural Intelligence EngineProfessional solution
Spatial evidence for decisions that depend on place.
We connect geospatial inputs, analytical methods and practical interpretation while keeping hypotheses distinct from field measurements and professional judgment.
Problems we help solve
Location questions are often blocked by inconsistent coordinates, incomplete addresses, disconnected GIS and CAD files, or satellite observations that need context before they can support action.
- Persistent variability and change across landscapes
- Spatial risk and regulatory overlays
- Property, territory and location intelligence
- GIS/CAD interoperability and georeferencing
Data and analytical inputs
Depending on the question, inputs may include multitemporal Earth Observation, Sentinel-2 imagery, spectral indices, administrative and urban datasets, geocoded points, FEMA NFHL layers, property context, field observations or weather-informed environmental signals.
- Raster and vector processing
- Coordinate-system and georeferencing validation
- Change detection and temporal normalization
- Spatial statistics, clustering and enrichment
Outputs and deliverables
Outputs can include decision-ready maps, statistics, classified zones, spatial risk overlays, enriched datasets, engineering-compatible geometry, reports or environmental exposure tools such as the Animal Heat Stress Analyzer.
- Maps and compact technical reporting
- Validated GIS/CAD-compatible data
- Property and location context
- Reusable spatial workflows
Methodological controls
Satellite-derived patterns and modeled environmental values are evidence layers, not direct field measurements. They support where to look, what to investigate and how to compare locations; professional domain judgment and local observation remain necessary for conclusions and action.
- Separate observed, inferred and contextual values
- Document source, date, coordinate system and processing assumptions
- Keep uncertainty visible and avoid unsupported diagnosis or prediction
Related work
BGPD, the Urban Geocoded Dataset, FEMA integration, property intelligence and ITH show how spatial analysis becomes a usable decision layer.