Dr. George Ashiagbor

Senior Lecturer


Dept: Nature Conservation and Applied Geoinformatics
Dept. of Wildlife and Range Management
Faculty of Renewable Natural Resources
Ground Floor
Room 151

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Research Areas/Interests

  Forest cover mapping, monitoring and regulatory compliance — baseline forest/non-forest mapping, independent validation of national la...~more

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Research Areas/Interests

 

  1. Forest cover mapping, monitoring and regulatory compliance — baseline forest/non-forest mapping, independent validation of national land-cover products, deforestation-free commodity supply chains, EU Deforestation Regulation due diligence, and REDD+ measurement, reporting and verification.
  2. Agro-commodity expansion and land-use change — the advance of cocoa, rubber, cashew and oil palm into forest and food-crop land; displacement of food cropland and its consequences for farmer food self-sufficiency; land-sparing and land-sharing as policy responses.
  3. Mining-driven land degradation — time-series mapping of artisanal and small-scale gold mining inside and outside forest reserves, landscape pattern change, and the downstream effects of mining on cropland, yield and water quality.
  4. Habitat, biodiversity and conservation planning — habitat connectivity and fragmentation modelling, habitat quality assessment, species distribution modelling, and the use of small mammals and odonata as indicators of anthropogenic disturbance.
  5. Carbon stocks and climate-change mitigation — aboveground carbon dynamics under agro-commodity cultivation, carbon storage potential of vegetation on mining concessions, and carbon enhancement through tree crops and agroforestry.
  6. Precision agronomy and UAV remote sensing — multispectral unmanned aerial systems for crop mapping and nutrient monitoring, soil fertility archetyping for site-specific nutrient management, shade-tree canopy optimisation, and pre-visual detection of Cocoa Swollen Shoot Virus Disease.
  7. Watershed and water resources assessment — GIS-based ecohydrological risk modelling, sediment yield under landscape change, and multi-criteria decision analysis for river basin management.
  8. Geospatial methods and geo-information science — machine-learning and deep-learning classifiers for complex agroforestry mosaics, object-based image analysis, radar and vegetation-phenology approaches to species mapping, and cellular automata–neural network land-change simulation.

 

 


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