[New index for crop canopy fresh biomass estimation].
Bibliographic record
Abstract
The objective of the present study is to propose a new vegetation index for corn canopy fresh biomass estimation, which improves the ability to accurately estimate high biomass levels by remote sensing technology. For this purpose, hyperspectral reflectance data of corn canopies were collected using a ground-based spectroradiometer during different field campaigns in a region of Quebec (Canada), from 2004 to 2008. Corresponding fresh biomass values were obtained by destructive measurements, and a hyperspectral image was also acquired using the Compact Airborne Spectrographic Imager (CASI) in 2005. A new biomass index named red-edge triangular vegetation index (RTVI) was designed and compared to existing indices used for fresh biomass estimation. The results showed that RTVI was the best vegetation index for predicting canopy fresh biomass, with sustained sensitivity at high fresh biomass levels. The best regression model between RTVI and canopy fresh biomass was the power fit, with determination coefficient (R2) of 0.96. With the validation by CASI imagery in 2005, good results were obtained. The relationship between CASI predicted biomass and actual biomass was 0.58 (R2), with the RMSE of 0.44 kg x m(-2).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".