If a settlement is not on the map,
it is not in the plan.
MSS maps settlements, facilities and the geography between them, then converts that geography into planning decisions. This is the technical core of the Geo-ST4R programme in Kano State.
Health planning usually works from estimated catchment populations. Estimates cannot show that a cluster of households sits four kilometres past the last scheduled outreach point.
Map settlements and verify facility locations first, then let catchment, accessibility and gap analysis be derived from that geography — so planning decisions reference places that exist.
Nine geospatial service areas.
Each service below feeds the same objective: a planning process that reflects where people actually live.
Settlement Mapping
Identification and geolocation of communities, including dispersed and seasonal clusters that administrative lists omit.
Health Facility Mapping
Verification of facility coordinates and service points — the reference layer for every catchment and proximity question.
Geospatial Microplanning
Translation of mapped geography into outreach session plans, delivered through the Geospatial Microplanning Toolkit (GMT).
Geographic Catchment Analysis
Assignment and review of facility catchments so that responsibility for a settlement is explicit rather than assumed.
Community Accessibility Assessment
Travel distance, road condition and seasonal access considered together, because proximity on a straight line is not access.
Spatial Data Visualisation
Legible layered maps for planners and decision forums — designed to be read by programme staff, not only GIS specialists.
Coverage Gap Identification
Systematic flagging of settlements and clusters without an assigned service point or a scheduled session.
Geographic Resource Planning
Placement questions for teams, outreach posts and commodities, informed by settlement distribution rather than administrative symmetry.
Zero-Dose Identification Support
Spatial evidence that helps programmes locate where unimmunised children are most likely to be concentrated.
See how settlement-level geography exposes gaps.
Toggle settlement and facility layers, then observe which communities sit beyond an assigned catchment. All points are synthetic and labelled as illustrative — this is a demonstration of planning logic, not operational programme data.
Geospatial Microplanning — Illustrative Demo
Kano State • Settlement & facility layers • Synthetic data — not operational GMT data
What the map shows
Traditional microplanning uses estimated catchment populations. GMT uses mapped settlement locations so teams plan against real geography — not assumptions.
Legend — Illustrative Layers
How GMT helps
- •Visualise every settlement relative to facilities
- •Identify missed clusters beyond perceived catchments
- •Assign sessions to real places, not estimates
- •Track coverage at settlement-level granularity
Data Integrity Notice
All points and boundaries are synthetic illustration to demonstrate capability. No confidential government, patient or programme dataset is displayed.
How this lands in a facility.
The practical difference between a capability described and a capability delivered.
Planning-grade data
Maps are built to withstand use at a planning meeting: clear layers, current facility points, and gaps stated instead of implied.
Geography as a workflow
Teams correct the map as they use it, so accuracy improves through routine planning rather than periodic surveys.
Readable by non-specialists
Layer design assumes the reader is a health worker or programme manager, not a cartographer.
Honest about uncertainty
Where settlement data is incomplete, that incompleteness is stated — an unmapped area is treated as a question, not an absence.
Discuss this capability with MSS.
Share your geography, programme and timeline — we will recommend an entry point and what to expect.