SEA is a region where conventional forest carbon methodologies frequently fall short due to its ecological complexity and fragmented land-use patterns.
Home to around 15% of the world’s tropical forests, the region plays a critical role in climate mitigation by removing and storing carbon from the atmosphere.
Yet many existing carbon measurement frameworks are not calibrated to capture the variability of the landscapes, increasing the risk of data inaccuracy and undermining environmental integrity.
“Tropical forests are a crucial carbon sink. To make more effective decisions on how to protect and manage these ecosystems, we need better data. Measuring forest biomass and forest carbon isn’t a problem that’s unique to South East Asia, but there are many challenges that are specific to our region,” said Dr Götz Martin, CEO Nature Based Solutions, Golden Agri-Resources (GAR).
The project seeks to overcome the shortcomings of traditional manual biomass measurement methods, which are often labour-intensive and susceptible to error.
“For example, commonly used models for measuring forest biomass rely on manual measurements. For a conservation area located in an Indonesian peatland – potentially covering thousands of hectares – this can mean a two- or three-day trek through difficult and sometimes dangerous conditions to take sample measurements.
“It’s not always safe, it’s not efficient, and it’s hard to come back to the same spot to make accurate comparisons year after year. These methods were also built on European forest types and don’t account for the complex tropical forest landscapes where we operate,” said Martin.
GAR’s partnership with Arkadiah seeks to address these data gaps through the deployment of advanced Digital Monitoring, Reporting and Verification (DMRV) technologies.
“Arkadiah’s technology helps to solve these problems of access and accuracy, using techniques that can pinpoint specific sample areas and give a much more accurate picture of above-ground biomass,” said Martin.
Advancing forest monitoring
The five-year project will focus on West Kalimantan, Indonesia, to improve the scientific accuracy and transparency of tropical forest carbon assessments.
The companies aim to build scalable, high-resolution datasets capable of supporting more credible carbon accounting.
The project will integrating high-resolution satellite imagery with aerial and ground-based Light Detection and Ranging (LiDAR) scans, AI-driven geospatial modelling and hydrological analysis to generate 3D digital twins of forest areas.
This would enable longitudinal tracking of changes and more robust carbon sequestration estimates over time.
“South East Asia’s forests are highly biodiverse and variable, which makes carbon measurement especially complex. Arkadiah’s approach combines AI modelling with satellite imagery, aerial LiDAR and terrestrial LiDAR. This multi-modal approach generates precise, highly auditable datasets that capture tree-level structure while reflecting variability across large landscapes,” said Reuben Lai, CEO, Arkadiah.
Regional climate support
This initiative was announced on February 2 at the inaugural Singapore Space Summit. It will be supported under Singapore Economic Development Board (EDB)’s Corporate Venture Launchpad programme, which facilitates collaboration between multinational corporations and startups.
The Office for Space Technology and Industry (OSTIn), Singapore’s national space office, is also backing the project, reflecting growing interest in the role of satellite and geospatial technologies in climate infrastructure.
As part of the collaboration, GAR and Arkadiah plan to publish technical insights and methodological learnings to inform best practices in high-integrity carbon measurement.
By sharing their frameworks, the partners aim to contribute to broader climate mitigation efforts and reinforce Singapore’s position as a regional hub for carbon services and sustainability innovation.
Lai said: “Over the next 12 months, we will implement on-ground baselining and carbon assessment with these integrated measurements. In the longer term, we aim to contribute technical insights that strengthen industry standards and expand this work across GAR’s landscapes.”
