Quantifying Peatland Land Use and CO2 Emissions in Irish Raised Bogs: Mapping Insights using Sentinel-2 Data and Google Earth Engine

This research combines Sentinel-2 satellite imagery with machine learning algorithms implemented in Google Earth Engine to classify land use patterns and estimate CO₂ emissions from Irish raised bog peatlands.

Key Findings

• Successfully mapped land use categories across Irish raised bogs using Sentinel-2 multispectral data
• Quantified CO₂ emissions associated with different peatland management practices
• Developed scalable methodology for national-scale peatland monitoring
• Contributed spatial datasets supporting climate-related peatland management decisions

Methodology

The study employed cloud-based processing in Google Earth Engine to analyze multi-temporal Sentinel-2 imagery, enabling efficient processing of large-scale satellite datasets for environmental monitoring applications.

This work provides critical insights into peatland carbon dynamics and their climate implications, supporting national greenhouse gas reporting and peatland conservation strategies.

Recommended citation: Habib, W., Ruchita, I., Saunders, M., & Connolly, J. (2024). "Quantifying Peatland Land Use and CO2 Emissions in Irish Raised Bogs: Mapping Insights using Sentinel-2 Data and Google Earth Engine." Scientific Reports, 14, 1171.
Download Paper