Estimation of grassland CO<sub>2</sub>exchange rates using hyperspectral remote sensing techniques
Bibliographic record
Abstract
Although the link between CO2 exchange and spectral reflectance is well established in laboratory conditions, limited research has been conducted in the field. To determine the applications of remote sensing in the estimation of the northern mixed grasslands as a carbon sink, the primary objective of this study was to evaluate several narrow‐band vegetation indices and band depth analysis in the prediction of leaf CO2 exchange rates in a northern mixed grass prairie ecosystem. Spectral reflectance and CO2 exchange measurements were collected from 13 sites located in Grasslands National Park, Saskatchewan, Canada. Pearson's correlation found a significant relationship between the CO2 exchange rates and the Photochemical Reflectance Index (PRI). Linear regression showed that the PRI explained 46% of the variance seen in the leaf CO2 exchange rates. This is somewhat lower than previous experiments conducted in laboratory conditions; however, the current study was conducted in field conditions, where there are a number of different species in the field of view and background effects from soil, litter and dead materials, which are negligible in laboratory conditions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".