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
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».