I build geospatial solutions that turn satellite imagery, spatial data, and AI into actionable insights for real-world problems.

My work sits at the intersection of Geospatial Intelligence, Earth Observation, Remote Sensing, GIS, Python, GeoAI, climate resilience, disaster risk, and open mapping.

Maps tell us where. Data tells us what. GeoAI helps us understand why — and what happens next.

• 🛰️ Earth Observation & Remote Sensing — extracting insights from Sentinel-1/2, Landsat, DEMs and other EO datasets
• 🗺️ Geospatial Development — building GIS applications, APIs, spatial databases and web mapping solutions
• 🤖 GeoAI & Machine Learning — applying ML/DL to satellite imagery, classification, prediction and spatial analysis
• 🌊 Climate & Disaster Risk — flood monitoring, hazard assessment, climate resilience and environmental modelling
• 🏙️ Urban Analytics — urban heat islands, land-use/land-cover, urban growth and spatial intelligence
• 🌍 Open Mapping — OpenStreetMap, HOT, humanitarian mapping and community-driven geospatial data
• 🐍 Geospatial Python — automation, spatial analysis, raster/vector processing and reproducible workflows

I'm particularly interested in building geospatial systems around:

🌊 Flood Risk & Hydrology Near-real-time flood monitoring, flood hazard modelling, hydrological analysis and disaster response.

🌡️ Urban Climate & Heat Urban Heat Island detection, environmental modelling and climate-resilient cities.

🛰️ Earth Observation & GeoAI Deep learning, computer vision and scalable AI workflows for satellite imagery.

🌍 Climate Resilience Using geospatial intelligence to understand climate risks and support adaptation planning.

🗺️ Open Geospatial Data OpenStreetMap, humanitarian mapping, community mapping and geospatial data quality.

Enhancing Disaster Response and Resilience through Near-time GIS for Flood Monitoring and Analysis

A geospatial workflow combining:

Sentinel-1 · Sentinel-2 · Landsat · SRTM · NDWI · LULC · WorldPop · OSM · Google Earth Engine

The project explored flood extent, environmental impacts, exposed populations and infrastructure to support disaster response and resilience planning.

Research applying open-source deep learning and Earth Observation to detect and analyse Urban Heat Island patterns.

Technologies include:

Sentinel-2 · Python · TensorFlow · U-Net · Attention Mechanisms · GeoAI

Worked on large-scale building footprint validation and quality assurance across Nigeria and Côte d’Ivoire, contributing to climate-resilience mapping through open geospatial data.

Tools included:

OpenStreetMap · HOT · QGIS · JOSM · GeoPandas · Python · Satellite Imagery

A Python-focused geospatial toolkit for spatial analysis and geospatial workflows.

A GIS platform concept for improving location intelligence, addressing and geospatial accessibility.

Earth Observation workflows for flood detection, exposure analysis and disaster-risk assessment.

Deep-learning approaches for detecting and analysing urban heat patterns using satellite imagery.

I'm open to:

🌍 Geospatial collaborations 🛰️ Earth Observation projects 🤖 GeoAI & ML research 🌊 Climate & disaster-risk projects 🗺️ Open mapping initiatives 💻 Geospatial software development

Building geospatial intelligence that helps people understand places, predict risks, and make better decisions.

Where GIS meets Earth Observation, AI, and real-world impact. 🌍🛰️🤖

Thanks for visiting my profile — let's build something geospatial.