Measurements relating fire radiative energy density and surface fuel consumption – RxCADRE 2011 and 2012
Bibliographic record
Abstract
Small-scale experiments have demonstrated that fire radiative energy is linearly related to fuel combusted but such a relationship has not been shown at the landscape level of prescribed fires. This paper presents field and remotely sensed measures of pre-fire fuel loads, consumption, fire radiative energy density (FRED) and fire radiative power flux density (FRFD), from which FRED is integrated, across forested and non-forested RxCADRE 2011 and 2012 burn blocks. Airborne longwave infrared (LWIR) image time series were calibrated to FRFD and integrated to provide FRED. Surface fuel loads measured in clip sample plots were predicted across burn blocks from airborne lidar-derived metrics. Maps of surface fuels and FRED were corrected for occlusion of the radiometric signal by the overstorey canopy in the forested blocks, and FRED maps were further corrected for temporal and spatial undersampling of FRFD. Fuel consumption predicted from FRED derived from both airborne LWIR imagery and various ground validation sensors approached a linear relationship with observed fuel consumption, which matched our expectation. These field, airborne lidar and LWIR image datasets, both before and after calibrations and corrections have been applied, will be made publicly available from a permanent archive for further analysis and to facilitate fire modelling.
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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 | 0.001 | 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 | 0.001 |
| 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".