Use of middle infrared radiation to estimate the leaf area index of a boreal forest
Bibliographic record
Abstract
The leaf area index (LAI) of boreal forest can be estimated using reflected radiation recorded by satellite sensors. Measurements of visible and near infrared radiation are commonly used in the normalized difference vegetation index (NDVI) to estimate LAI. However, research, mainly in tropical forest, has demonstrated that LAI is related more closely to radiation of middle infrared wavelengths than of visible wavelengths. This paper derives a vegetation index, VI3, based on radiation from vegetation recorded at near and middle infrared wavelengths. For a boreal forest canopy, the relationship between VI3 and LAI was observed to be much stronger than that between NDVI and LAI. In addition, the LAI estimated using VI3 accounted for about 76% of the variation in field estimates of LAI, compared with about 46% when using the NDVI. We conclude that information provided by middle infrared radiation should be considered when estimating the leaf area index of boreal forest.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".