Peatland Mapping

How does our peatland mapping work?

Using satellite imagery as fine as 50 cm, we apply custom-trained AI models to classify peatland extent, identify habitat variation, and track ecosystem change.

We can monitor features such as dry vs wet peat, invasive tree encroachment (e.g. Sitka spruce), vegetation type (mosses, sedges, bog woodland), and structural patterns like pools or peat cuttings.

Why is peatland mapping important?

Peatland mapping refers to the remote sensing and classification of peatland ecosystems. It includes delineating peatland extent, categorising habitat types, and assessing condition indicators like vegetation cover, microtopography, and moisture levels.

Peatlands store twice as much carbon than all the world’s forests combined. When healthy, they regulate water, support biodiversity, and provide critical ecosystem services. When degraded, they become major carbon sources.

Monitoring peatland condition is essential to climate, biodiversity, and land management goals.

Key aspects of peatland mapping

Peatland mapping focuses on identifying and assessing the extent, type, and condition of peatland habitats. Key aspects include:

• Extent Mapping – Defining the boundaries of peatland areas using imagery and ecological indicators.

• Habitat Classification – Distinguishing between peatland types (e.g. bog, fen) and associated vegetation communities.

• Condition Assessment – Evaluating indicators like vegetation cover, water levels, bare peat, erosion, and tree encroachment.

• Change Detection – Monitoring restoration progress or degradation over time through repeat assessments.

• Integration with Standards – Aligning outputs with frameworks like the Peatland Code, TNFD, or biodiversity credit schemes.

Why choose Gentian?

Gentian combines deep expertise in ecology and AI with experience mapping peatlands across the UK, Ireland, and North America. We are actively developing the UK’s most advanced remote peatland condition monitoring system.

Our approach incorporates the Peatland Condition Matrix (PCM), field-validated datasets, and machine learning workflows tailored for peatland features. We help restoration bodies, certifiers, and land managers get credible, science-based data, quickly and cost-effectively.