On the potential of MODIS and MERIS for imaging chlorophyll fluorescence from space
Bibliographic record
Abstract
The first images from MODIS (Moderate Resolution Imaging Spectroradiometer) are now being used to evaluate information on the in vivo fluorescence peak near 685 nm from chlorophyll-a, stimulated by sunlight. The Fluorescence Line Imager (FLI) airborne imaging spectrometer was used in the 1980s to demonstrate the mapping of this signal from an aircraft, showing that it gave significant rejection of confusing signals from atmospheric radiance. For imaging from space, a major limitation is sensor sensitivity, which tends to restrict imaging to relatively high concentrations under good solar illumination. Noise-equivalent chlorophyll concentrations for MODIS and MERIS (Medium Resolution Imaging Spectrometer) have been estimated as 0.07 and 0.1 mg m−3, respectively, under zenith Sun, clear sky conditions. Although MERIS has slightly poorer sensitivity, it has the advantage of flexible band placing and presence of a band at 709 nm in the baseline band-set that allows better definition of the continuum spectrum above which fluorescence is measured. This band should also allow detection of bright plankton blooms (red-tide events) through the peak radiance near 709 nm caused by a combination of in-water scattering and absorption.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".