Objectives of the service
Sust Global is developing a geospatial AI platform to unlock unique insights on carbon project permanence, durability and sequestration potential for global forest and blue carbon projects. This new analytics platform, Regen Atlas, increases transparency, trust and uptake of carbon credits in the nature finance space. Our analytics of global forest and blue carbon projects provides accurate forward-looking data on emergent sequestration risks from physical climate risk (e.g. wildfire or water scarcity), pests and insects, seismic risks and potentially other types of risk such as geopolitical instability. Regen Atlas transforms complex layers of geospatial, satellite and risk data into metrics on project durability and permanence. This service provides cost-savings through de-risking project investment, create trust in carbon markets, and ultimately accelerate sustainable forestry and blue carbon project deployment.
Our data products take satellite derived observations, proprietary climate models, and new geospatial datasets on biodiversity, biomass and water scarcity. These datasets are fused using machine learning and computer vision-based AI techniques for high cadence, high quality carbon offset risk analytics at global scale.
Users and their needs
The targeted user communities include carbon project investors, carbon project developers, advisory firms, and carbon credit marketplaces. These users are located primarily in Europe and North America, with an initial focus on markets in the UK, the US, and Canada.
Service/ system concept
Regen Atlas provides advanced analytics to help users assess carbon credits by offering detailed insights into sequestration potential, durability metrics, and risk assessments. The system enables users to visualize geospatial data for carbon projects, generate customizable project-level summaries, and compare multiple projects for risk and return analysis. Additionally, the platform introduces the “Sust Score,” a standardized measure of credit quality designed to improve transparency and facilitate transactions in carbon credit markets.
The system works by leveraging satellite imagery and machine learning to analyse carbon project data. Users can upload project boundaries or explore preloaded demo projects through a user-friendly interface or programmatically via an API. Regen Atlas processes the data to produce actionable outputs, such as spatial risk analysis and sequestration predictions, helping users make informed decisions about project quality and value.
At a high level, the system integrates satellite data, global fire databases, and land cover maps into a cloud-based processing layer. This layer uses machine learning models for bias correction and advanced predictions. The results are delivered through a web interface and API, providing seamless access to summaries, visualizations, and standardized scoring metrics for carbon credit evaluation.
Space Added Value
Regen Atlas leverages satellite data as a key space asset, integrating high-resolution imagery from Sentinel-2, ESA CCI Land Cover, and global fire datasets like GFEDv4 and GFAS from ECMWF. These space-based data sources enable accurate, large-scale assessments of carbon sequestration potential and durability metrics that are crucial for evaluating the quality of carbon credits. By using satellite-powered analytics, Regen Atlas delivers consistent, unbiased, and up-to-date insights that are not easily replicated through traditional methods.
The added value of combining these space assets lies in their ability to provide global coverage and high-frequency observations, offering granular geospatial data that traditional on-the-ground methods cannot achieve at scale. Space assets also reduce dependency on manual data collection, which can be costly, inconsistent, and subject to localized biases. Regen Atlas’s machine learning models further enhance the utility of satellite data by correcting biases and generating actionable predictions, such as risk assessments and sequestration estimates, with >60% accuracy. Competitive offerings will rely on static, present day analytics, whereas Regen Atlas will provide high resolution, globally accurate and forward-looking analytics.
Current Status
The Regen Atlas project is progressing steadily, with significant milestones already achieved. We have conducted over 10 Climate Data Studios across key markets, engaging stakeholders from carbon project investors, developers, and advisory firms to thoroughly scope user requirements. These sessions provided invaluable insights into the challenges and needs of our target users, shaping the platform’s development.
Recently, we successfully completed our Baseline Design Review (BDR), which validated the technical and commercial feasibility of the platform’s core features, including geospatial analytics, sequestration potential assessments, and the “Sust Score.”
Prime Contractor(s)
