Ghana wildfire monitoring and susceptibility
Long-run burned-area analysis, active-fire comparison, district heterogeneity, open research data and a developing national susceptibility framework.
View Ghana fires researchResearch
Research
Applied research in wildfire science, Earth observation, environmental monitoring, remote sensing and geospatial systems
Applied evidence
Research connected to environmental decisions and technical practice
Nana Ekow Nkwa Sey’s research combines environmental engineering, Earth observation, geospatial analysis and machine learning. The work is grounded in reproducible data practices and connected to practical experience in satellite ground systems, UAV operations and research infrastructure.
The principal programme examines fire dynamics and wildfire susceptibility in Ghana. Complementary themes extend to environmental monitoring, applied remote sensing and environmental modelling.
Research themes
Five connected areas of work
Each theme has a distinct purpose. Satellite ground systems are presented primarily as professional and technical work, while UAV applications span both research and practice.
Earth observation and environmental monitoring
Satellite, geospatial and field observations used to characterise environmental conditions, change and risk.
Satellite ground systems
Technical operations, infrastructure and data-service support for satellite reception, communications and institutional research.
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UAV and remote-sensing applications
Aerial data acquisition, photogrammetry, environmental assessment and machine-learning applications using remotely sensed imagery.
Environmental modelling
Data-driven models for environmental risk, spatial prioritisation and transparent decision support.
Research pathway
From observations to usable evidence
The website presents research as a traceable progression rather than a collection of disconnected outputs.
- ObserveAcquire and document satellite, UAV, environmental and operational data.
- HarmoniseAlign spatial units, time periods, definitions and quality controls.
- AnalyseApply appropriate spatial, statistical and machine-learning methods.
- ExplainSeparate established evidence, uncertainty and work still under review.
- ApplyPublish reusable data, research tools and decision-relevant outputs.
Research standards
Principles used across the programme
Reproducibility and provenance
Public outputs are linked to documented data sources, defined spatial units, support periods and quality checks.
Sensor honesty
Burned area and active-fire detections are treated as related but different observations rather than interchangeable measures.
Responsible claims
Published evidence is distinguished from completed work under review, ongoing research and planned outputs.
Accessible communication
Methods and limitations are explained for technical and non-technical readers without concealing uncertainty.