Notice bibliographique
Résumé
In many regions of the world, fires are the primary environmental disturbance producing a mosaic of burned and unburned patches varying at temporal and spatial scales and providing a variety of ecosystem services. Fire perimeters mark the separation between the burned and unburned matrix of a fire. In prior studies in the United States, Australia, and Alberta, variations in the fire environment, fuel, weather, topography, and anthropogenic factors, affected fire perimeter formation. One of the critical challenges in interpreting and comparing regional variations in the fire cessation process is that each study employs a different sample distance and analysis technique. In this study, I examined fire cessation in the western Canadian Rocky Mountain region, where no fire extinguishment studies have been undertaken despite human values at risk facing increased fire hazards. This study investigates how fire environment factors influence fire cessation on the 2017 Verdant Creek Fire in Kootenay National Park. The Verdant Creek Fire is ideally suited to this research as it burned under a variety of environmental conditions, with a varying application of suppression techniques. This work evaluated the performance of 16 distances of analysis for comparing exterior unburned areas with interior burned areas to identify how static variables influence fire cessation. Two spatial and temporal scales assessed the influence of weather on fire boundary formation. The potential influence of fire suppression on fire cessation was also examined. Data were extracted using GIS and analyzed with statistical modelling using matched case-control conditional logistic regression. Predictive fire boundary models were compared to determine the effectiveness of different distances of analysis and predictor variables. Results indicated that fire boundary formation was strongly influenced by fuel composition, arrangement, and to a limited extent, topography. Weather influenced fire boundary formation, but mainly in areas where suppression occurred. Suppression was successful in periods of diminished weather conditions, and areas near waterways. The influence of vegetation was largely consistent regardless of the implementation of suppression tactics. While results from the weather model have applications in operational fire management, occurring over a limited period (1–14 days), the stable fire environment model has applications in strategic planning as it uses variables that are relatively consistent over extended periods (1–5 years). Results from the best sample distance were used to develop a Spread Potential Index (SPI). The SPI was used to map the probability of fire spread. The SPI has potential uses in strategic fire management activities as a tool for rapid visual assessment on the influence of temporally stable fire environmental factors on fire cessation.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».