Explore traceable population, climate, environmental and service evidence across Nigeria's 8,809 wards. Compare local conditions and identify what needs closer investigation.
Search. Review. Compare. Investigate. Prepare.
Search by ward name or use phone location to identify your ward.
Estimated population
25,803people
NNPIS V3 derived estimate · 2026
Surface heat
+7.95 °C
Tree cover
0.0%
Ward boundary
Available
Population is a derived estimate. Surface heat is daytime land-surface temperature, not air temperature.
Why wards
Conditions can differ significantly between wards within the same LGA. Smart Ward makes those local differences visible without turning incomplete evidence into false certainty.
Broad summaries can conceal meaningful differences between neighbouring wards.
Useful information sits across reports, geospatial datasets, catalogues and technical systems.
A number may be an estimate, proxy, historical observation or incomplete record.
One LGA, different local conditions
A single LGA average can look uniform while its wards tell different evidence stories.
Ward 1
Dense settlement
01Ward 2
Higher heat signal
02Ward 3
More tree cover
03Ward 4
Fewer mapped services
04Ward evidence preserves local differences while keeping sources, periods and limitations visible.
36 + FCT
States and Federal Capital Territory
774
Local Government Areas
8,809
Canonical wards
Planning becomes more responsible when evidence is organised around the places where people experience decisions.
From place evidence to decisions
Smart Ward preserves identity, definition, source, period, coverage and limitations throughout the workflow.
Resolve a canonical ward by name, LGA, state or phone location.
Find a canonical ward
Balogun Fulani 1
Ilorin South LGA, Kwara State
Canonical identity resolved
Examine available population, climate, environmental, built-form and service evidence.
Ward evidence profile
Estimated population
25,803
Climate history
Available
Land cover
Mapped
Service records
Reviewed
Sources, periods, units, coverage and limitations remain visible.
Align definitions, units and periods across selected wards or an entire LGA.
Ilorin South comparison
Estimated population, NNPIS V3, 2026
Individual measurements describe differences. They are not an overall ward ranking.
Apply a planning lens to identify observations, evidence gaps and field-review questions.
Climate resilience lens
Which heat signals need field review?
Where is service evidence incomplete?
What local conditions are not captured?
Evidence gaps remain visible and become part of the field-review plan.
Use Mowa to prepare a grounded explanation, checklist or planning draft.
Prepared with Mowa
Evidence summary
The selected wards show different surface-heat and tree-cover signals. Review local shade, built form and current conditions before drawing a heat-risk conclusion.
Smart Ward supports investigation. It does not automatically rank wards, allocate resources or replace fieldwork.
Evidence transparency
Smart Ward distinguishes sourced records, derived estimates, historical observations, proxy measurements and unavailable evidence so users can understand what each value supports.
Returned by an identified catalogue
Calculated using a documented method
Observed for a stated past period
Supports screening, not a direct conclusion
Kept visible instead of becoming zero
Evidence trace
Estimated population
25,803
people
Classification
Derived estimate
Source
NNPIS V3
Reference year
2026
Unit
People
Coverage
Complete
Known limitation
Derived estimate, not a census count. The 2026 projection is distributed using the documented NNPIS V3 methodology.
Evidence groups
Each group retains its own definition, source, reference period, coverage and limitations.
Canonical geography
01Population and demographics
02Climate history
03Surface heat
04Terrain and historical water
05Vegetation and land cover
06Settlement and built form
07Roads and mapped services
08Solar context
09Missing information remains visible as a limitation. It is not silently converted into zero or removed from the interface.
Ward comparison
Compare selected wards or every ward within the same LGA while retaining definitions, units, periods, sources and coverage.
Ilorin South comparison workspace
Balogun Fulani 1
ReferenceBalogun Fulani 2
Balogun Fulani 3
At a glance
NNPIS V3, 2026, derived estimate
Balogun Fulani 1Reference
25,803
Balogun Fulani 2
24,613
Balogun Fulani 3
30,289
Go deeper
Values retain their definitions, units, periods, sources and limitations.
Demographics
Population and age groups
Environment
Heat, vegetation and water
Built Form
Settlements and roads
Services
Health, schools and markets
Climate and Terrain
History, elevation and slope
Decision packs
Packs organise evidence for investigation. They do not rank wards or make allocation decisions.
Climate resilience
Heat, terrain, water, land cover and historical climate
Health and essential services
Population, mapped services, roads and settlement evidence
Clean energy and connectivity
Solar context, settlement form, roads and remaining evidence gaps
Comparison describes differences in individual measurements. It is not an overall ward ranking and does not determine which ward should receive an intervention.
Evidence-grounded AI agent
Mowa is Smart Ward's evidence-grounded AI agent. It works with one ward, selected wards or an entire LGA, then returns findings connected to their supporting measurements.
Evidence-backed observations
Ward and metric citations
Source and reference-period context
Confidence and availability status
Evidence limitations
Field-review questions
Structured planning drafts
Mowa
Evidence-grounded AI agent
Evidence context
Balogun Fulani 1, 2 and 3, Ilorin South
Which selected wards should planners examine more closely for combined surface-heat and low tree-cover signals?
Evidence-grounded responseBalogun Fulani 1 and 2 both have no mapped tree-cover share and show slightly higher wet-season surface-heat departures than Balogun Fulani 3. These signals support closer local review, not a final heat-risk conclusion.
Surface heat
+7.95 °C, +8.00 °C and +7.49 °C
MODIS daytime LST, 2020–2025
Tree cover
0.0%, 0.0% and 17.8%
Mapped land cover, 2021
Surface heat is daytime land-surface temperature, not air temperature. Tree-cover data does not measure street-level shade.
Field-review question
Do current shade, building materials and street conditions support the satellite evidence?
A factual statement must match approved evidence.
Server rules verify differences, highest and lowest values.
Missing evidence cannot be presented as a finding.
Raw provider answers are not returned directly.
Sensitive location data is not exposed.
Mowa helps users examine evidence. It does not make allocation decisions or replace professional judgement.
Built for shared local understanding
Communities, planners, institutions and partners can work from the same canonical geography while asking different questions.
Communities and civic organisations
Smart Ward can support them to
Review a plain-language ward profile
Connect local questions to visible sources and limitations
Prepare evidence for participation and follow-up
Local knowledge remains essential. Smart Ward provides a shared evidence reference for discussion.
LGA planning teams
Smart Ward can support them to
Compare selected wards or the complete LGA
Apply a planning lens to aligned evidence
Record evidence gaps and field-review questions
Comparison supports planning discussion. It does not automatically rank wards or allocate resources.
State and national institutions
Smart Ward can support them to
Use one canonical State, LGA and ward hierarchy
Review consistent evidence definitions across places
Identify where additional local assessment is required
Ward evidence adds local context to wider programmes without replacing statutory datasets or processes.
Development and humanitarian partners
Smart Ward can support them to
Examine population, environment and mapped services
Check coverage before interpreting apparent gaps
Prepare questions for partners and field teams
Mapped evidence supports early scoping. Delivery feasibility and current need still require local validation.
Researchers and responsible enterprises
Smart Ward can support them to
Review traceable multi-domain ward evidence
Compare measurements with their provenance intact
Identify limitations before further analysis
Smart Ward provides a first-stage evidence foundation, not a substitute for specialist research or due diligence.
Planning lenses available
Climate resilience
Heat, rainfall, terrain, water, vegetation and settlement form
Health and essential services
Population, mapped services, roads and settlements
Clean energy and connectivity
Solar context, settlement form, roads and evidence gaps
A planning lens organises evidence for review. It does not approve, reject or rank an intervention.
The evidence foundation remains consistent even when the decision context changes.
Start with one ward
Search a canonical ward, inspect the available evidence and identify what deserves closer investigation. Sources, coverage and limitations remain part of the answer.
Live geospatial and AI services may be paused between scheduled demonstrations. The public landing-page showcase remains available.
