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We use lidar scanners to measure biomass at scale. We’ve laser scanned over 16 million tropical rainforest trees in Gabon and Peru, and will be building on this dataset as we conduct more research trips.
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We provide independent and unbiased ratings you can trust
Corporate sustainability leaders, traders and asset managers around the world rely on Sylvera’s carbon ratings and market intelligence to achieve their climate goals.
We don’t sell carbon credits.
We are not paid by developers to rate projects.
Transparency
Our frameworks are public so buyers understand exactly what we test and how we do it, and peer-reviewed by esteemed Framework Review Committees, made up of scientific experts and carbon market stakeholders.
Depth
Access the most comprehensive assessments of carbon projects available today. Project reports provide granular analysis of core project characteristics, insightful data visualizations, and interactive maps.
Visibility
View the whole market of carbon credits at a macro level, or dive deep into individual project performance. Compare quality, price and co-benefits to find the highest-rated credits for the best value.
Our Edge
The Sylvera difference
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Project-type-specific frameworks
We believe one-size-fits all frameworks produce unreliable results.
That’s why we build meticulous frameworks for every project category to accurately test project design, carbon accounting, and climate impact claims.
Unparalleled rigor and accuracy
We extract, clean, and organize data from project design documentation (PDD) and every monitoring report.
We meticulously build carbon, strength of baseline and financial additionality models from the ground up.
Independent Data Validation
Our expert analysts leverage advanced machine learning (ML) technology, verified, independent data, and proprietary field data to test the accuracy of credit issuances and claims.
CUTTING-EDGE TECHNOLOGY
We’re building the world’s largest and most accurate dataset on carbon stored in natural ecosystems
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Our estimates of the above-ground biomass and carbon stored in forests are up to 13x more accurate than conventional estimates derived from methods known as allometrics.
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We use this first-of-its-kind data to train advanced machine learning models, which use Earth observation data to estimate carbon stocks from space, in near real-time and with great accuracy.
Ratings Methodology
Biochar Framework
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For each project type, Sylvera develops a proprietary framework to assess carbon credit quality. This paper outlines our ratings framework for biochar projects.
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