Potential of MODIS EVI and surface temperature for directly estimating per‐pixel ecosystem C fluxes
Bibliographic record
Abstract
We tested the potential of estimating per‐pixel gross primary production (GPP) directly from the MODIS enhanced vegetation index (EVI) and respiration directly from MODIS surface temperature (MOD11). Carbon flux data were obtained from 10 eddy covariance tower sites representing a wide range of North American vegetations. The correlation between across‐site tower GPP and EVI was comparable (r = 0.77) to that between tower GPP and MOD17‐GPP (r = 0.73), suggesting that EVI could be used to provide reasonably accurate direct estimates of GPP on a truly per‐pixel basis. There was also a strong relationship (r2 = 0.67) between respiration and surface temperature of dense vegetation, suggesting that estimation of net ecosystem exchange (NEE) may be possible with relatively simple pixel based models, at least for some vegetation types.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".