An OpenStreetMap (OSM)-driven geospatial accessibility dashboard for evaluating healthcare and education access across Akure North and Akure South, Nigeria. Features multi-modal travel analysis (walking, motorcycle/okada, and driving), accessibility scoring, service coverage assessment, and OSM data-completeness. Built for Map<>kathon 2026.
# Mapping the Gap: Health & Education Accessibility in Akure
**Live dashboard:**
akure-accessibility-dashboa… · **GitHub:**
github.com
An OSM-driven accessibility analysis for Akure North and Akure South
LGAs (Ondo State, Nigeria), built for **Map<>kathon 2026** (Dashboard
or Analysis track). Consumes OSM data - and its accompanying extraction
manifest - produced by the companion
**Nigerian LGA OSM Extractor** tool and turns
it into a health/education access-deficit analysis with an integrated
OSM completeness check, facility-type classification, parameterized
assumptions with a built-in sensitivity analysis, and an interactive
dashboard that reports uncertainty honestly rather than hiding it.
> **How this serves the public good:** this project uses OSM's own
> road and facility data to identify which communities in Akure North
> and South lack practical access to healthcare and education, across
> walking, okada, and driving, and, critically, distinguishes genuine
> service gaps from places where OSM itself simply hasn't caught up
> yet. Treating an OSM data gap as a confirmed service gap could
> misdirect real planning attention, so every finding this project
> presents is labeled as one of four honest categories - served,
> confirmed underserved, potential OSM data gap, or unknown - rather
> than presenting a single number as certain.
## Headline findings
Walking is the most restrictive mode in both LGAs, by a wide margin:
| | Akure North | Akure South |
|---|---|---|
| Underserved for ≥1 service (walking) | 95.0% of settled cells | 83.2% of settled cells |
| Underserved for both services (walking) | 59.7% | 60.8% |
| Avg. health facility travel time (walking) | 80 min (median 47) | 53 min (median 39) |
| % of cells exceeding the 30-min threshold | 68.1% | 63.7% |
These headline numbers use the project's baseline assumptions (see
`akure_access/config/default.yaml …