Urban & Regional Planner · GIS & Remote Sensing · Spatial Decision Support
Planning better places with geospatial data.
LinkedIn · Email · GitHub · Nigeria
I am an Urban and Regional Planner interested in how geospatial analysis can support better decisions about cities, infrastructure, environmental change and access to services. My work spans urban growth modelling, land-use change, flood risk, transport and healthcare accessibility, drought monitoring, land suitability, conflict and displacement, coastal vulnerability and urban green infrastructure. Across these projects, I combine GIS, remote sensing, spatial modelling, network analysis and machine learning with one consistent goal: turning spatial evidence into clear, useful planning insight.
| Case study | Planning question | Key evidence / approach |
|---|---|---|
| Ibadan — Land-use change & urban expansion | How has Ibadan changed between 2013 and 2023? | Built-up land increased from 99.866 km² to 330.177 km²; final locked holdout: 14/16 correct. |
| Abuja — Urban-growth scenario | Where could Abuja's urban footprint expand by 2035? | Historical LULC transitions, CA–Markov modelling and urban-growth suitability were combined to develop a planning scenario. |
| Lokoja — Flood hazard & risk | Where is flood hazard concentrated, and how robust is the result? | AHP/MCDA combined terrain, rainfall, drainage, land cover and exposure evidence with validation and sensitivity testing. |
| Lagos — Public transport accessibility | Who can reach formal transit within 30 minutes on foot? | 46.56% of the analysed population fell outside the threshold or behind a structural network gap. |
| Kano — Primary healthcare accessibility | Where is primary healthcare access weakest? | Analysis covered 1,584 PHCs, 484 wards and 16,789 demand cells using network accessibility, 2SFCA and scenario testing. |
| Northern Nigeria — Drought & vegetation monitoring | Where is vegetation declining without a matching rainfall decline? | MODIS vegetation indices and CHIRPS rainfall were used for long-term vegetation–rainfall trend analysis. |
| Enugu — Near-urban expansion suitability | Where is observed near-urban expansion more likely? | Extra Trees modelling, spatial validation and suitability mapping were used to examine expansion patterns. |
| Borno — Conflict & displacement | Where do multiple indicators point to settlement contraction or change? | VIIRS night-time lights, ACLED conflict events, WorldPop and displacement evidence were examined together. |
| Tartu — Green-infrastructure deficit | Where does local ecosystem-service demand exceed green capacity? | Sentinel-2, Dynamic World and spatial indicators were combined to map relative green-infrastructure deficit. |
| Ayetoro — Coastal vulnerability | Which buildings face the greatest relative coastal vulnerability? | 72.17% of 1,628 buildings fell in High or Very High relative-vulnerability classes. |
I start with the planning question, then choose the data and method around it. I separate observed evidence from model output, validate assumptions where possible and state limitations clearly. If a later review shows that an earlier result is weak, I would rather rebuild it than keep a polished result I cannot defend.
GIS & Remote Sensing — ArcGIS/ArcMap · QGIS · Google Earth Engine · Landsat · Sentinel-2 · MODIS
Python & Spatial Computing — GeoPandas · Rasterio · Pandas · NumPy · scikit-learn · OSMnx · NetworkX · Matplotlib
Planning Analysis — change detection · network accessibility · 2SFCA · CA–Markov · AHP/MCDA · suitability modelling · vulnerability assessment
My practical experience includes land-use analysis, environmental assessment, neighbourhood planning and GIS-supported site studies. I have also trained university IT students in practical GIS applications and participated in community sensitisation around a proposed transport project.
I am interested in graduate study, research collaboration and early-career opportunities involving GIS, remote sensing, climate adaptation, coastal management, urban resilience, accessibility and spatial decision support.
Explore the case studies above for methods, maps, validation, code and planning interpretation.