Hazard Monitoring Agent
Watches hazard feeds and triggers activation thresholds
Tool: Flood extent model · Source: Optical and SAR imagery
Industry
Conceptual visualization onlyDisaster management AI agent operations
Emergency operations centre with satellite, weather, hazard and evacuation layers
Operational layers in view
Satellite imageryWeather dataFlood extentHazard zonesExposed populationEvacuation routes
Hazard Monitoring Agent
Flood Intelligence Agent
Satellite Change Agent
Exposure Agent
Evacuation Agent
Emergency Coordination Agent
Node activity below is a demonstration using sample disaster management data.
Emergency outputs are decision support for authorised agencies. Alerts, evacuations and public communications are only issued after an accountable coordinator approves them.
Ask the live agents
Describe the problem in your own words. We classify the industry, assign specialist agents, and you watch the workflow run and produce the visual deliverables — maps, dashboards, charts, tables and reports — instead of one block of text.
Demo mode uses clearly labelled sample data — never presented as verified.
Assigned specialists
Disaster management
- Hazard Monitoring Agent
- Flood Intelligence Agent
- Satellite Change Agent
- Exposure Agent
- Evacuation Agent
- Emergency Coordination Agent
Deliverables planned
Interactive map
Timeline
KPI panel
Data tables
Recommendations
Pauses for human approval
Emergency coordinator approval
Emergency outputs are decision support for authorised agencies. Alerts, evacuations and public communications are only issued after an accountable coordinator approves them.
Workflow the run follows
- 1. User request
- 2. Requirement validation
- 3. Industry classification
- 4. Specialist agent selection
- 5. Data and file collection
- 6. Tool authorisation
- 7. Execution plan
- 8. Multi-agent collaboration
- 9. Analysis or generation
- 10. Quality validation
- 11. Human approval
- 12. Visual deliverables
- 13. Monitoring and audit
Demo
Disaster management AI agent operations centre
Workflow: Hazard alert received → Monitor event · Run pending · started — · elapsed 0s
Active agents
0
Tasks running
0
Completed steps
0/9
Tool calls
0
Human approvals
1
Warnings
0
Success rate
0%
Est. completion
36s
Active agents
Pending
Flood Intelligence Agent
Derives inundation extent and depth from imagery
Tool: Flood extent model · Source: Optical and SAR imagery
Satellite Change Agent
Compares pre- and post-event scenes for damage
Tool: Flood extent model · Source: Optical and SAR imagery
Exposure Agent
Quantifies exposed population and critical assets
Tool: Flood extent model · Source: Optical and SAR imagery
Workflow canvas
Live activity stream
No activity yet. Start the demo run to watch disaster management agents work through the workflow with sample data.
Demonstration using sample data — no real client operation is shown. Sign in and connect an approved AI provider and authorised industry data source to activate live execution.
Disaster management specialist agents
Each agent owns one step of the workflow, with its own tools, inputs and approval level.
Autonomous
Hazard Monitoring Agent
Watches hazard feeds and triggers activation thresholds
- Inputs:
- Optical and SAR imagery, Weather and hydrology feeds, Population grids
- Tools:
- Flood extent model, Change detection, Exposure calculator
Autonomous
Flood Intelligence Agent
Derives inundation extent and depth from imagery
- Inputs:
- Optical and SAR imagery, Weather and hydrology feeds, Population grids
- Tools:
- Flood extent model, Change detection, Exposure calculator
Autonomous
Satellite Change Agent
Compares pre- and post-event scenes for damage
- Inputs:
- Optical and SAR imagery, Weather and hydrology feeds, Population grids
- Tools:
- Flood extent model, Change detection, Exposure calculator
Autonomous
Exposure Agent
Quantifies exposed population and critical assets
- Inputs:
- Optical and SAR imagery, Weather and hydrology feeds, Population grids
- Tools:
- Flood extent model, Change detection, Exposure calculator
Approval required
Evacuation Agent
Plans routes and shelter allocation
- Inputs:
- Optical and SAR imagery, Weather and hydrology feeds, Population grids
- Tools:
- Flood extent model, Change detection, Exposure calculator
Approval required
Emergency Coordination Agent
Prepares the agency briefing and alert package
- Inputs:
- Optical and SAR imagery, Weather and hydrology feeds, Population grids
- Tools:
- Flood extent model, Change detection, Exposure calculator
Solution blueprint
Operational context
Industry challenges
- Operational data for disaster management is spread across disconnected systems
- Analysis-heavy work is repeated manually every cycle
- Risks and exceptions are found late
- Reporting and audit overhead grows with volume
Solution patterns
Recommended AI solutions
- Specialist agents that own one step of the workflow each
- Grounded retrieval over your permitted systems only
- Predictive scoring with explainable reasons
- Approval-gated execution into your systems of record
Data readiness
Required data
- Optical and SAR imagery
- Weather and hydrology feeds
- Population grids
- Critical infrastructure registers
Controlled process
Example workflow
- Hazard alert received
- Validate feeds and imagery
- Derive flood extent
- Detect change and damage
- Compute exposure
Connection points
Integration opportunities
- National hazard feeds
- GIS services
- Alerting platforms
- Agency coordination systems
Measure after baseline
Expected outcomes
- Analysis cycle time
- Manual review effort
- Decision auditability
- Earlier risk detection
Governance controls
Security and compliance
- Row-level security scopes every read to the requesting organisation
- Retrieval is limited to documents the user may already open
- Every agent action, tool call and approval is written to the audit log
- Sensitive steps pause until a named human approves them
Inputs, integrations and outputs
Inputs
- • Optical and SAR imagery
- • Weather and hydrology feeds
- • Population grids
- • Critical infrastructure registers
Integrations
- • National hazard feeds
- • GIS services
- • Alerting platforms
- • Agency coordination systems
Outputs
- • Hazard extent map (GeoJSON, PDF)
- • Exposure summary (CSV, PDF)
- • Evacuation and shelter plan (PDF, GeoJSON)
Business outcomes to baseline and measure
Analysis cycle time
Target and measurement method agreed during discovery.
Manual review effort
Target and measurement method agreed during discovery.
Decision auditability
Target and measurement method agreed during discovery.
Earlier risk detection
Target and measurement method agreed during discovery.
No performance result is promised before a baseline is measured. Targets are agreed for each engagement and reported against real delivery data.
How This AI Agent Works
The process the disaster management agent team follows, from trigger to approved deliverable.
Earth observation workflow
From a study area and date range to a specialist-reviewed map and chart set.
Workflow preview
Saved with the run so the recorded execution trail shows what was asked. Demonstration runs use sample data. They do not touch your systems.
Public visitors can preview the structure and inspect every node. Labelled demonstrations and live runs require a signed-in account with configured providers.
72%
Workflow summary as a text list
- 1. Define study area and dates: Input. Draw or upload the area of interest and the observation window.
- 2. Discover imagery: Approved tool. Search the approved satellite archives for matching scenes.
- 3. Filter cloud coverage: Validation. Drop scenes above the cloud threshold and report coverage.
- 4. Preprocess imagery: Approved tool. Mask, mosaic and reproject the retained scenes.
- 5. Run analysis: AI agent. Compute indices or classification over the prepared stack.
- 6. Validate results: Validation. Check against reference samples and report accuracy.
- 7. Specialist review: Human approval. A remote-sensing specialist approves before release. Human approval required.
- 8. Map and charts: Output. Result layer, time-series charts and export package.
Approval gate: Specialist review. Deliverable: Map.
Workflow audit for this page
Structure only. Run a demonstration to include events.
| Template ID | Nodes | Approval node | Output type | Preview | Demo | Live | Mobile test |
|---|---|---|---|---|---|---|---|
| earth-observation-workflow | 8 | Yes. Policy: always | Map | Available | Available (signed in) | Available via Studio · requires ai_provider, python_service, earth_engine | Verified at 390px |
Demonstration runs are stored and replayed from recorded events. Live runs execute server-side in the Studio and only start when the listed integrations report healthy.
Relevant case study
Illustrative case study
Wastewater network GIS for a national water utility
A wastewater network needed utility-GIS structuring, mapping and quality-controlled network intelligence for daily operations.
View all case studiesReady to scope your AI initiative?
Share your objective and constraints. A specialist reviews every request before any recommendation is issued.