Mediterranean fire danger classes based on the Canadian Forest Fire Weather Index System, taking into account the Fire Radiative Power products from SEVIRI/MSG satellite
Bibliographic record
Abstract
Fire danger rating systems (FDRS) are widely used across the world for many purposes from planning for daily deployment of fire suppression resources to the evaluation of fire management strategies. FDRS can also be incorporated in different types of models and regions to assess the short and long-term effects of specific fire regimes and fire management policies. The Canadian Forest Fire Weather Index System (FWIS) is a widely known FDR system, being extensively applied for fire danger early warning in several regions around the world, namely over Europe. The FWIS includes a set of six sub-indices, based on meteorological data, to predict fire weather danger and fire behavior over regions under study. In order to have a reliable assessment of the fire danger based on the FWIS it is essential to define the most suitable threshold values for each danger class of the FWIS sub-indices over different regions. To establish those limit values for each class of the FWIS sub-indices, historical percentiles were computed for the period understudy, taking into account the occurred fire events (hotspots), despite the lack of information regarding fire events history and its relation to FWIS sub-indices. To accomplish the proposed validation, our approach is based on Fire Radiative Energy (FRE) released by each fire event that occurred in the Mediterranean region, over the study period. The FRE is computed from Fire Radiative Power (FRP) product as obtained from MSG/SEVIRI, generated and disseminated in near real-time by EUMETSAT in the framework of Land Surface Analysis Satellite Applications Facility (LSA SAF). Since FRP estimates the radiative power emitted by a given fire, it can be linked to local fuel burned amounts and be used as a proxy of fire intensity. By integrating FRP measures emitted during the lifetime of the fires that occurred over the regions under study, an estimate of the total FRE released can be easily obtained for each event. To obtain the FRE data for this work, it was considered the period of available FRP/SEVIRI data, from March 2010 to October 2021. Thresholds values of each defined danger class for the FWI, FFMC and ISI indices were calculated considering the total FRE hotspots registered, in agreement with the different fire regimes of the Mediterranean region. Since extreme wildfire patterns in Southern Mediterranean countries have been increasing over the last years, FRP/FRE products are a key tool to monitor and to improve fire managing activities, preparedness-including planning for deployment of fire suppression resources, over affected regions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".