Overview#
When a major sporting fixture draws 80,000 people into a city centre, a control room supervisor needs more than a static map. The Geospatial Workspace gives operators a live, layered operational picture: active unit positions, crowd density estimates, weather overlays, and dynamically recalculated risk zones, all on a single canvas. Decisions about where to pre-position ambulances or redirect foot patrols are made before an incident occurs, not after.
Predictive Analytics extends that picture into the near future. Machine learning models trained on historical incident data, seasonal patterns, and real-time environmental feeds generate demand forecasts and hotspot heatmaps that update continuously throughout a shift. Supervisors gain actionable lead time, enabling proactive resource deployment rather than reactive scrambling.
Key Features#
- Interactive Layered Map: Operators can toggle independent map layers including geofences, weather alerts, flood risk polygons, road closures, and dynamic risk zones without losing their operational context.
- Predictive Demand Heatmaps: Machine learning models combine historical incident density, event calendars, weather forecasts, and real-time signals to forecast where and when demand will rise, allowing units to be positioned ahead of the curve.
- Real-Time Unit Tracking: All field resources are visible with live position, heading, speed, and estimated time of arrival, giving control rooms a continuous picture of coverage and gaps.
- Spatial Queries and Clustering Analysis: Operators and analysts can run on-demand geographic queries to identify incident clusters, measure response-time coverage, or support post-incident forensic review.
- Geofence Alerting: Configurable boundary triggers notify operators automatically when assets enter or leave defined zones, supporting both operational tasking and compliance monitoring.
- Weather and Environmental Overlays: Live meteorological data including wind, precipitation, and flood modelling is displayed directly on the operational map to inform deployment decisions during severe-weather incidents.
- Multi-Layer Transparency Controls: Each data layer carries independent opacity and visibility controls so operators can customise the map to match the task at hand without creating visual noise.
- After-Action Playback: Incident timelines can be replayed geospatially, supporting debriefs, training, and evidence gathering.
Use Cases#
- Major Event Management: Pre-positioning ambulances, police, and fire resources around a stadium or concert venue based on predicted crowd movement corridors and historical demand from comparable events.
- Severe Weather Response: Tracking approaching storm fronts and flood risk contours in real time, allowing supervisors to redistribute resources to vulnerable areas before conditions deteriorate.
- Search and Rescue Coordination: Displaying search sectors, team positions, and terrain overlays on a shared map canvas so multiple agencies can coordinate without duplicating effort or creating gaps in coverage.
- Cross-Border and Multi-Agency Operations: Providing a common operational picture for joint deployments where each participating organisation sees a view scoped to its own assets and data while shared situational elements remain visible to all authorised parties.
- Demand Forecasting for Shift Planning: Using weekly and seasonal heatmap predictions to inform roster planning and vehicle deployment schedules, reducing reactive overtime and improving response-time targets.
Integration#
The Geospatial Workspace connects to the broader operational platform through standard geospatial and data exchange protocols. Live unit telemetry is consumed from the dispatch and communications layer, keeping the map in continuous sync with field activity. External meteorological feeds arrive via REST and streaming interfaces, and the predictive model engine draws on the same incident records used by reporting and analytics modules. Export of map snapshots and annotated incident data is available in open formats suitable for after-action reporting systems and external partner platforms.
Open Standards#
- OGC Web Map Service (WMS) and Web Feature Service (WFS): Map layers are rendered and queried using the Open Geospatial Consortium WMS and WFS standards, ensuring compatibility with third-party GIS platforms and national mapping infrastructure.
- GeoJSON (RFC 7946): All boundary definitions, geofences, and incident geometries are stored and exchanged as GeoJSON, the IETF-standardised format for geographic features in JSON.
- OGC Moving Features (OGC 14-083r2): Unit telemetry and asset tracking data follows the OGC Moving Features encoding standard, enabling interoperability with allied tracking and common operating picture systems.
- EPSG:4326 / WGS 84 (ISO 19111): The platform uses WGS 84 as its primary coordinate reference system, aligned with ISO 19111 and universally compatible with GPS, NATO geographic standards, and civil GIS tooling.
- ETSI EN 303 413: Location information exchange within emergency communications follows ETSI standards for terrestrial location of mobile devices, relevant to integration with national emergency call infrastructure.
- STANAG 2586 (APP-6D): Military symbol sets displayed on joint-agency operational maps use NATO APP-6D symbology where interoperability with defence partners is required.
- OGC API Features (OGC 17-069r4): The geospatial query interface exposes feature collections through the OGC API Features standard, allowing external consumers to retrieve incident geometry and asset data over standard HTTP without proprietary client libraries.
- ISO 19107 (Spatial Schema): Geometric types and topological relationships used internally conform to the ISO 19107 spatial schema, ensuring that spatial queries produce results consistent with recognised geographic computing standards.
Availability#
- Enterprise Plan: Included
- Professional Plan: Core map and unit tracking included; predictive heatmaps and advanced spatial analytics require upgrade to Enterprise.
Last Reviewed: 2026-05-26