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Spatial and temporal variability in forest fire behavior, caused by differences in microsites, fuel types and condition, topography, and other factors across even relatively small areas, has been poorly characterized in most previous studies. Past characterization of forest fires has often been limited by monitoring techniques that relied on timing systems in coarse-resolution sampling grids. We report documentation and analysis of fire behavior for several experimental fires using a camcorder-sized infrared camera mounted in a helicopter hovering over the target fires. These fires were conducted as part of the Russian FIRE BEAR Project in boreal Pinus sylvestris L. forests of central Siberia. Final results provide quantitative information on fire front location, rates of spread, temperatures, and total radiation energy (kW/m 2 ) observed during the fires at resolutions from 2.5 to 1.0 m across experimental burn plots ranging from 2.3 to 4.0 ha. Further postfire analysis using GIS produced a detailed spatial and temporal quantification of fireline intensity (kW/m) across the plot area. This type of infrared monitoring and analysis helps to support clearer assessment of relationships between fire behavior and ecological impacts. Such data permit accurate fire behavior estimates at various temporal and spatial scales rather than using an overall plot average. This method allows the sample size to be quite large, so that statistical analysis of the fire behavior data can provide an associated level of confidence.Résumé : Les variations spatiale et temporelle dans le comportement des incendies de forêt causées par les différences entre les microsites, les types et l'état des combustibles, la topographie et d'autres facteurs, même sur des superficies relativement restreintes, ont été mal caractérisées dans la plupart des études précédentes. Dans le passé, la caractérisation des incendies de forêt a souvent été limitée par les techniques de suivi qui dépendaient de systèmes de chronométrage dans des mailles d'échantillonnage de faible résolution. Nous présentons la documentation et l'analyse du comportement du feu pour plusieurs feux expérimentaux à l'aide d'une caméra infrarouge de la dimension d'un caméscope montée dans un hélicoptère faisant du surplace au-dessus du feu à étudier. Ces feux ont été provoqués dans le cadre du projet russe FIRE BEAR dans les forêts boréales de Pinus sylvestris L. du centre de la Sibérie. Les résultats finaux fournissent des informations quantitatives sur la localisation du front de feu, le taux de propagation, la température et l'énergie totale de rayonnement (kW/m 2 ) observés pendant les incendies avec une résolution de 2,5 à 1,0 m dans des parcelles expérimentales de 2,3 à 4,0 ha. D'autres analyses faites subséquemment aux incendies à l'aide d'un système d'information géographique ont produit une quantification détaillée dans le temps et dans l'espace de l'intensité (kW/m) à la ligne de feu à travers la superficie de la parcelle. Ce type de suivi et d'analyse avec l'infrarouge aide ...

The Canadian Forest Fire Weather Index (FWI) system was evaluated for the Daxing'anling region of northern China for the 1987-2006 fire seasons. The FWI system reflected the regional fire danger and could be effectively used there in wildfire management. The various FWI system components were classified into classes (i.e. low to extreme) for fire conditions found in the region. A total of 81.1% of the fires occurred in the high, very high and extreme fire danger classes, in which 73.9% of the fires occurred in the spring (0.1, 9.5, 33.3 and 33.1% in March, April, May and June). Large wildfires greater than 200 ha in area (16.7% of the total) burnt 99.2% of the total burnt area. Lightning was the main ignition source for 57.1% of the total fires. Result show that forest fires mainly occurred in deciduous coniferous forest (61.3%), grass (23.9%) and deciduous broad leaved forest (8.0%). A bimodal fire season was detected, with peaks in May and October. The components of FWI system were good indicators of fire danger in the Daxing'anling region of China and could be used to build a working fire danger rating system for the region.Additional keywords: fire management support systems, fire regime, fire weather.

Two fixed-threshold (CCRS and ESA) and three contextual (GIGLIO, IGBP, and MODIS) algorithms were used for fire detection with Advanced Very High Resolution Radiometer (AVHRR) data acquired over Canada during the 1995 fire season. The CCRS algorithm was developed for the boreal ecosystem, while the other four are for global application. The MODIS algorithm, although developed specifically for use with the MODIS sensor data, was applied to AVHRR in this study for comparative purposes. Fire detection accuracy assessment for the algorithms was based on comparisons with available 1995 burned area ground survey maps covering five Canadian provinces. Overall accuracy estimations in terms of omission (CCRS=46%, ESA=81%, GIGLIO=75%, IGBP=51%, MODIS=81%) and commission (CCRS=0.35%, ESA=0.08%, GIGLIO=0.56%, IGBP=0.75%, MODIS=0.08%) errors over forested areas revealed large differences in performance between the algorithms, with no relevance to type (fixed-threshold or contextual). CCRS performed best in detecting real forest fires, with the least omission error, while ESA and MODIS produced the highest omission error, probably because of their relatively high threshold values designed for global application. The commission error values appear small because the area of pixels falsely identified by each algorithm was expressed as a ratio of the vast unburned forest area. More detailed study shows that most commission errors in all the algorithms were incurred in non-forest agricultural areas, especially on days with very high surface temperatures. The advantage of the high thresholds in ESA and MODIS was that they incurred the least commission errors. The poor performance of the algorithms (in terms of omission errors) is not only due to their quality but also to cloud cover, low satellite overpass frequency, and the saturation of AVHRR channel 3 at about 321 K. Great improvement in global fire detection can probably be achieved by exploring the use of a wide variety of channel combinations from the data-rich MODIS instruments. More sophisticated algorithms should be designed to accomplish this.