Deriving forest canopy fuel parameters for loblolly pine forests in eastern Texas
Bibliographic record
Abstract
Crown fires, the fastest spreading of all forest fires, can occur in any forest type throughout the world. The overall aim of this study was to estimate forest canopy fuel parameters including canopy bulk density and canopy base height for loblolly pines ( Pinus taeda L.) at the plot level using both allometric equations and CrownMass/FMAPlus software. Allometric equation results were compared with the CrownMass outputs for validation. According to our results, the calculated average canopy bulk density values, across all 50 plots, were 0.18 and 0.07 kg/m3 for the allometric equation and the CrownMass program, respectively. Lorey’s mean height approach was used in this study to calculate canopy base height at the plot level. The average height values of canopy base height obtained from the Lorey height approach was 10.6 m and from the CrownMass program was 9.1 m. The results obtained for the two methods are relatively close to each other, with the estimate of canopy base height being 1.16 times larger than the CrownMass value. This study provides a practical method for quantifying these parameters and making them directly available to fire managers. The accuracy of these parameters is very important for realistic predictions of wildfire initiation and growth.
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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 | 0.001 |
| 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".