EarthDaily Constellation: daily global scientific quality imagery for environmental monitoring
Bibliographic record
Abstract
The EarthDaily Constellation (EDC), planned to be operational in early 2025, is a revolutionary Earth observation system designed to provide daily global coverage of the Earth's landmass with scientific-grade data. The mission's origins can be traced back to the agriculture sector, where there was a pressing need for high-quality, frequent Earth observation data to support critical decisions. Over time, the mission evolved to address a wide range of environmental applications including water management, forestry, disaster response, wildfire risk and wildfire propagation, greenhouse gas monitoring, and more. EDC addresses the need for more frequent, higher-resolution scientific-quality monitoring to understand and mitigate the impacts of climate change.The ten-satellite constellation, equipped with 22 spectral bands ranging from visible to long-wave thermal infrared, will collect an unprecedented 100 TB of data per day with a 10-year design life.The spectral bands have been carefully modeled after Landsat-8/9 and Sentinel-2 to ensure compatibility with historical archives, supporting long-term studies of Earth's evolution, and maximizing the value for environmental monitoring
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".