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The objectives of this study are to evaluate landscape-scale fuel and terrain controls on fire rate of spread (ROS) estimates derived from repetitive airborne thermal infrared (ATIR) imagery sequences collected during the 2017 Thomas and Detwiler extreme wildfire events in California. Environmental covariate data were derived from prefire National Agriculture Imagery Program (NAIP) orthoimagery and USGS digital elevation models (DEMs). Active fronts and spread vectors of the expanding fires were delineated from ATIR imagery. Then, statistical relationships between fire spread rates and landscape covariates were analyzed using bivariate and multivariate regression. Directional slope is found to be the most statistically significant covariate with ROS for the five fire imagery sequences that were analyzed and its relationship with ROS is best characterized as an exponential growth function (adj. R2 max = 0.548, min = 0.075). Imaged-derived fuel covariates alone are statistically weak predictors of ROS (adj. R2 max = 0.363, min = 0.002) but, when included in multivariate models, increased ROS predictability and variance explanation (+14%) compared to models with directional slope alone.

An important property of wildfire behaviour is rate of spread (ROS). The objectives of this study are to evaluate the uncertainty of landscape-scale ROS estimates derived from repetitive airborne thermal infrared (ATIR) georeferenced imagery and the utility of such estimates for understanding fire behaviour and controls on spread rates. Time-sequential ATIR image data were collected for the Cedar, Detwiler, and Rey Fires, which burned in California during summers of 2016 and 2017. We analyse error, uncertainty, and precision of ROS estimates associated with co-location accuracy, delineation of active fire front positions, and generation of fire spread vectors. The major sources of uncertainty influencing accuracy of ROS estimates are co-registration accuracy of sequential image pairs and procedures for delineating active fire front locations and spread vectors between them; none of these were found to be substantial. Median ROS estimates are 11 m min−1 for the Cedar Fire and 8 m min−1 for the Detwiler Fire, both of which burned through mixed shrub and tree areas of the Sierra Nevada foothills and were estimated for downslope spread events. Of the three study fires, the fastest spread rates (average spread of 25 m min−1 with maximum of 39 m min−1) are estimated for the Rey Fire, which burned on variable directional slopes through chaparral shrubland vegetation.

The Cooney Ridge Fire Experiment conducted by fire scientists in 2003 was a burnout operation supported by a fire suppression crew on the active Cooney Ridge wildfire incident. The fire experiment included measurements of pre-fire fuels, active fire behavior, and immediate post-fire effects. Heat flux measurements collected at multiple scales with multiple ground and remote sensors illustrate the spatial and temporal complexity of the fire progression in relation to fuels and fire effects. We demonstrate how calculating cumulative heat release can provide a physically based estimate of fuel consumption that is indicative of fire effects. A map of cumulative heat release complements estimates of ground cover constituents derived from post-fire hyperspectral imagery for mapping immediate post-fire ground cover measures of litter and mineral soil. We also present one-year and 10-year post-fire measurements of overstory, understory, and surface conditions in a longer-term assessment of site recovery. At the time, the Cooney Ridge Fire Experiment exposed several limitations of current state-of-science fire measurement methods, many of which persist in wildfire and prescribed fire studies to this day. This Case Report documents an important milestone in relating multiple spatiotemporal measurements of pre-fire, active fire, and post-fire phenomena both on the ground and remotely.

Combustion emissions and strong Santa Ana winds had pronounced effects on patterns and levels of ambient ozone (O3) in southern California during the extensive wildland fires of October 2007. These changes are described in detail for a rural receptor site, the Santa Margarita Ecological Reserve, located among large fires in San Diego and Orange counties. In addition, O3 changes are also described for several other air quality monitoring sites in the general area of the fires. During the first phase of the fires, strong, dry and hot northeasterly Santa Ana winds brought into the area clean continental air masses, which resulted in minimal diurnal O3 fluctuations and a 72-h average concentration of 36.8 ppb. During thesecond phase of the fires, without Santa Ana winds present and air filled with smoke, daytime O3 concentrations steadily increased and reached 95.2 ppb while the lowest nighttime levels returned to w0 ppb. During that period the 8-h daytime average O3 concentration reached 78.3 ppb, which exceeded the federal standard of 75 ppb. After six days of fires, O3 diurnal concentrations returned to pre-fire patterns and levels.

Temperature, intensity, spread, and dimensions of fires burning in tropical savanna and slashed tropical forest in central Brazil were measured for the first time by remote sensing with an infrared imaging spectrometer that was designed to accommodate the high radiances of wildland fires. Furthermore, the first in situ airborne measurements of sensible heat and carbon fluxes in fire plumes were combined with remote measurements of flame properties to provide consistent remote-sensing-based estimators of these fluxes. These estimators provide a means to determine rates of fuel consumption and carbon emission to the atmosphere by wildland fires as required for assessments of fire impacts on regional air pollution or global emissions of greenhouse gases. Observed fires developed complex fire-line geometry and thermal structure, even as average whole-fire temperatures varied little. Flame temperatures sometimes exceeded 1600 K along the leading edge of actively spreading fire lines, yet >90% of the radiant energy from observed fires was associated with temperatures of 830–1440 K. Fire in a partially slashed forest encompassed a high-intensity flaming front and a trailing reach of residual combustion extending 400 m. Fire fronts in tropical savanna typically formed with little depth and a high proportion of their radiant flux density associated with high temperatures due to low levels of residual combustion. Measured fires had such low and variable radiance compared with that of a blackbody of comparable temperature as to preclude the use of fire radiance at a single wavelength as a measure of fire intensity or temperature. One-half of the radiant flux density from a measured savanna fire was associated with values of a combined emissivity–fractional-area parameter

In wildland fire management, reliable fire intelligence is needed to direct suppression resources, maintain firefighter safety, predict fire behavior, mitigate fire effects in the environment, and justify and evaluate the effectiveness of fuel management. Fire intelligence needs to be synoptic, quantitative, consistent, and timely. Airborne remote sensing with specialized infrared radiometers is now providing an unprecedented level of information on fire behavior and effects. The temperature, radiant intensity, carbon and sensible heat fluxes, and fuel consumption associated with the flaming front of a wildland fire have been estimated by remotely measuring its radiance at short- and mid-wave infrared wavelengths. Measurements of upwelling long-wave or thermal-infrared radiation provide estimates primarily of ground-surface temperatures, even beneath flaming fronts, that reflect a local time course of energy release and fuel consumption. Characteristics of flames and hot ground can be discriminated from radiances measured at wavelengths near 1.6, 3.9, and 11.9 μm. Fire radiance at 3.9 μm appears to be a good estimator of radiant-flux density, which integrates across wavelengths. There are strong temperature gradients along and within flaming fronts, and although their temperatures are high—commonly exceeding 1000°C along the line of a savanna fire, for instance—flames may not be bright when compared with a blackbody radiator. The combination of that low bulk emissivity and uncertainty as to the composition and radiance of nonfire background within the sensor's instantaneous field of view dictates that fire properties are best estimated from measurements of high spatial resolution in comparison with the scale of a fire front. The USDA Forest Service is now applying a FireMapper™ thermal-imaging radiometer for fire research and support of incident command teams over high-priority wildland fires, especially those threatening cities and communities in southern California. Resulting data are providing insight into fire behavior in complex and changing fuels, fire interactions with the atmosphere and a changing climate, and large-scale fire processes.