Historical context
Compare like periods and account for seasonal variation.
What it covers
Anomaly Detection capabilities
Spatial context
Find localized differences within a field or monitored area.
Triage
Rank unusual signals for evidence review and field follow-up.
Workflow
How it fits into operations
- 01
Frame the question
Choose a field, period, operational decision, and available evidence.
- 02
Assemble context
Bring together permitted imagery, indices, weather, water, and activity records.
- 03
Interpret
Generate a structured explanation, uncertainty, and proposed follow-up checks.
- 04
Review
Apply human and domain judgment before acting on a recommendation.
OutputsWhat teams can take forward
Anomaly list
Prioritized candidates with location and observation date.
Supporting context
Relevant imagery, trends, and uncertainty for review.
Interpretation and limitations
LAWA outputs are model-assisted interpretations, not guaranteed diagnoses, forecasts, or professional advice.
- Recommendations are only as reliable as the input data, assumptions, and model fit.
- Confidence and missing context should remain visible to the reviewer.
- High-impact decisions need qualified human review and field verification.
Put land intelligence to work
Create an account or sign in to explore the available Earthasoft workflow.
Create an account