Remote Sensing-Based Assessment of Fire Danger Conditions Over Boreal Forest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Forest fire is an integral part in many forested ecosystems including boreal forests, that influences forest productivity, biodiversity and socio-economy, among others. In this paper, we evaluated the potential of three selected satellite (i.e., MODIS)-based variables/indices at 8-day temporal resolution, i.e., surface temperature ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</sub> ), normalized multiband drought index (NMDI) and temperature vegetation wetness index (TVWI) in predicting/forecasting the fire danger conditions over boreal forest regions of Alberta during the period 2006-2008. The method was based on the assumption that the fire danger conditions during <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> +1 period would be high if the instantaneous values of: (i) <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</sub> values were either higher or equal; or (ii) NMDI or TVWI values were either lower or equal; with compare to their respective study-area-specific average during i period. The analyses were conducted on the basis of either individual variable or combining all of the three together. We found that 60.59% for <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</sub> , 72.41% for NMDI, and 54.19% for TVWI of fires fell under the high fire danger conditions. The combination of all of the three individual variables, it revealed that 91.63% of the fires fell in the categories of “very high” (i.e., all three variables indicated high danger), “high” (i.e., at least two of them indicated high danger), and “moderate” (i.e., at least one of the variables indicated high danger) fire danger classes. These results showed that the applicability of the proposed method in predicting fire danger conditions over the boreal forest regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 it