Temitope Waheeb

Extracted and structured OpenStreetMap infrastructure data using QuickOSM in QGIS and ArcGIS Pro, producing validated shapefile layers. Audited and documented 33 open geospatial data sources for Nigeria and built automated datasets with Python.

Produced flood risk maps using AHP and GIS-based multi-criteria decision making, and delineated groundwater potential zones by integrating VES data and remote sensing. Computed a Heat Risk Index for Ibadan and analysed land use/land cover change from 1983 to 2023.

Developed Python workflows using Pandas, GeoPandas, Matplotlib and Seaborn to clean, model and visualise climate and crop yield data across all 37 Nigerian states. Ran spatiotemporal analysis of climate change impacts on cereal yields and produced vulnerability and yield gap assessments.

Digitised land parcels in QGIS, converting survey plans and cadastral records into clean parcel polygon layers. Linked each parcel to supporting land documents in Mevron and georeferenced scanned survey plans.

Developed automated data processing workflows that cut turnaround time by 30 percent across recurring client jobs. Designed survey instruments and collection methodologies that achieved a 95 percent response rate with documented validity and reliability checks.

Built interactive dashboards and infographics in Power BI, Excel and Python that lifted stakeholder engagement with reporting by 25 to 35 percent. Ran descriptive and predictive analysis on operational data, supporting a 15 percent gain in operational efficiency.

Doctoral research ongoing alongside full-time professional work.

Grade: 6.05/7.0

M.Sc. in Geographic Information Science with a CGPA of 6.05/7.0. Awarded Best Master's Research Dissertation.

Grade: 3.15/4.0

B.Sc. in Geology with a CGPA of 3.15/4.0.