Using Earth Observation for UK Carbon Storage Monitoring and Future Geohazard Risk

Using Earth Observation for UK Carbon Storage Monitoring and Future Geohazard Risk

Engineering

Enzo Lim

2025

Enzo Lim and BGS

This project uses Earth Observation and InSAR satellite data to improve the mapping of peat thickness across Northern Ireland. By integrating terrain parameters such as slope, topographic position index (TPI), and topographic wetness index (TWI) with ground motion data, a semi-supervised machine learning approach was developed to distinguish areas of thin and thick peat. Improved spatial understanding of peat depth supports carbon accounting, geohazard risk assessment, and infrastructure planning in peatland regions. This research demonstrates how remote sensing can deliver cost-effective, scalable, and data-driven solutions for climate resilience and environmental monitoring. Peatlands are vital carbon stores that regulate hydrology and mitigate climate change, yet over 80% of UK peat is degraded and emitting carbon.

Earth Observation, machine learning, peatlands, carbon storage, remote sensing, InSAR, climate change mitigation, geohazard risk, spatial analysis, environmental monitoring.