Calterra wins £96,000 grant for habitat monitoring

Calterra has secured a £96,000 SMART Grant from Scottish Enterprise to support technology for monitoring restored peatlands and woodlands.

The funding will back a 14-month research and development project to improve the company's digital monitoring, reporting and verification capabilities. The work will focus on tracking the long-term health of habitats after restoration and reducing the cost and difficulty of measuring recovery over time.

Calterra is a joint venture between AI consultancy New Gradient and Caledonian Climate. The business uses artificial intelligence and Earth observation data to support habitat restoration projects, with much of its work so far focused on the earlier stages of restoration, such as land mapping and planning interventions.

The project marks a shift towards what happens after restoration begins. Calterra plans to work across both peatlands and woodlands as it develops tools intended to provide more regular, accurate assessments of habitat condition over longer periods.

The work comes against a wider policy backdrop in Scotland, where the Climate Change Plan has set a target to restore more than 400,000 hectares of peatland by 2040. The plan also outlines a new Peatland Standard designed to improve consistency and efficiency across restoration projects, including monitoring and verification.

For land managers, investors and public bodies involved in restoration, proving long-term outcomes has become increasingly important as more money flows into nature-based projects. Monitoring large areas can be expensive and time-consuming, particularly in remote landscapes, while verification standards are becoming more prominent as the market develops.

Ewan McMillan, Founder and Managing Director of New Gradient, said the project would extend Calterra's work beyond the initial stages of restoration.

"Most of our work with Calterra so far has been at the start of a restoration project: mapping the land and helping to plan what interventions are needed. This project is about what happens next.

"We want to be able to track the health of peatlands and woodland habitats over the long term, and do that more frequently, more accurately and at a lower cost, giving people greater confidence that restoration is actually delivering what it set out to do."

Accelerator selection

Separately, Calterra has been selected as one of 12 companies in Cohort 10 of the University of Edinburgh's AI Accelerator, delivered in partnership with Edinburgh Innovations. The programme supports AI businesses looking to scale and offers mentoring, commercial and investment advice, and access to academic and entrepreneurial networks.

The selection places Calterra among a group of young AI-focused companies supported through one of Scotland's better-known university-led programmes for early-stage growth. Since launching in 2019, the accelerator has supported more than 100 companies.

The combination of grant backing and a place in the accelerator comes at a time when demand for measurement in environmental markets is drawing greater scrutiny. Projects tied to peatland restoration, woodland recovery, and wider carbon or biodiversity outcomes increasingly rely on data to show whether interventions are producing the intended results.

Calterra's work is aimed at the gap between restoration activity on the ground and evidence of how ecosystems respond afterwards. By focusing on longer-term monitoring rather than only initial site assessment, the company is trying to address a part of the restoration process that can be harder to measure at scale.

Scotland's peatlands have become a particular focus for climate policy because of their role in storing carbon and supporting biodiversity. Degraded peatland can release emissions, while restoration is seen as an important part of wider climate and land-use goals, making reliable monitoring more central to public policy and project finance.

Woodland restoration raises similar questions around survival, condition and ecological change over time. In both areas, the ability to gather consistent data more frequently could affect how projects are assessed, funded and reported.