ESA Coastal Blue Carbon project: Towards Earth-Observation-based solutions for coastal blue carbon monitoring
Bibliographic record
Abstract
The international consensus on the urgent necessity to act to protect a vulnerable environment and endangered biodiversity raises key challenges, including the need to improve and accelerate estimating carbon stocks and changes in coastal ecosystems on a global scale. Remote sensing methods, combined with ground truthing and modelling, are essential for addressing this challenge cost-effectively.The ESA Coastal Blue Carbon project is an unprecedented effort to review, assess, and attempt to provide key elements for the sustainable management of Blue Carbon Ecosystems (BCEs) through diverse case studies. Over two years, a multidisciplinary consortium is investigating the mangrove, seagrass, and tidal salt marsh BCEs in France, Canada, Spain and French Guiana. The project aims to develop innovative tools and methods based on Earth Observation (EO) to estimate and monitor changes in carbon stocks, and brings together a community of end-users, to ensure the tools meet the operational needs, including:Conservation stakeholders aiming to enhance the impact of their actions. Decision-makers looking to integrate blue carbon into national carbon accounting and set ambitious mitigation targets. The financial sector seeking reliable blue carbon investment opportunities. Our rationale is to capitalise on existing data and multi-scale resolution imagery to assess the potential for global replicability of the space-based methodologies from highly representative pilot regions of the main BCEs across three different continents. The project consists of two phases: the first focuses on developing and consolidating requirements to create new methods on test areas, while the second emphasizes upscaling demonstration, and impact assessment. We aim at producing maps of carbon storage estimates for three different years from 2015 to 2025, with a spatial resolution no coarser than 10m while ensuring active participation from Early Adopters.The project has been submitted to be endorsed under the Global Ocean – Blue Carbon Programme of UNESCO Ocean Decade.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".