Enhancing ecosystems conservation through earth observation solutions, capacity development and co-design
Bibliographic record
Abstract
PEOPLE-ECCO (Enhancing Ecosystems Conservation through Earth Observation Solutions, Capacity Development and Co-design) is a project funded by ESA under the Earth Observation Science for Society (EO4Society) programme. The project answers to critical needs identified by Civil Society Organizations (CSOs) and Non-Governmental Organizations (NGOs) striving to improve evidence-based ecosystem conservation. The project aims to develop and demonstrate innovative Earth Observation (EO)-integrated methods and tools to 1) monitor protected areas conditions and management effectiveness, and 2) identify high-priority areas to be protected. PEOPLE-ECCO follows a co-design and user-centred approach. This means we develop the tools together with conservation CSOs/NGOs and provide tailored capacity development enabling them to integrate these EO methodologies in their operational practices. PEOPLE-ECCO commenced in October 2024 and will run for two years. In this presentation we will outline our overall approach which consists of two interacting parts: a user-focused part dedicated to user engagement, requirement consolidation and capacity development, and a technology-focused part focussing on EO-integrated methods and tools testing, development and demonstration. A central role is reserved for six NGOs/CSOs active in conservation actions with an interest in taking up EO solutions. These “Early Adopters” will jointly contribute to the development of actionable and relevant EO-integrated methods and tools. The Early Adopters in PEOPLE-ECCO (African Parks, Bulgarian Society for the Protection of Birds, Lebanon Reforestation Initiative, IUCN Vietnam, Prince Edwards Island Watershed Alliance and Reef Check Malaysia) are distributed over four continents, and the ecosystems they jointly manage cover a range of terrestrial and aquatic ecosystems. Outputs of PEOPLE-ECCO aim to contribute to the EU Biodiversity Strategy for 2030 and the Kunming-Montreal Global Biodiversity Framework (GBF), especially to GBF Target 3 (Conserve 30 percent of land, water and seas) and Target 20 (Strengthen Capacity-Building, Technology Transfer, and Scientific and Technical Cooperation for Biodiversity).
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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 | 0.036 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".