Wildfires are worsening in Canada and globally, partly due to climate change. The government of Canada is designing and building WildFireSat, the world’s first purpose-built operational satellite system for wildfire monitoring. It will provide new fire intelligence to support decision-making. It takes time for fire management agencies to use new information: to understand it and its implications, change processes, develop training, and modify computer systems. Preparing for the system’s prelaunch will allow agencies to benefit more rapidly from the new information. We present (1) an assessment of the readiness of 12 Canadian fire management agencies to integrate WildFireSat information and (2) guidance for reducing readiness gaps. We used survey and other data to score readiness indicators for three readiness components: understanding, organization, and information technology. We weighted the influence of each indicator score on each component. We modelled scoring and weighting uncertainties and used Monte Carlo simulation to generate distributions of aggregated agency readiness. The results indicated that most agencies have a moderate level of readiness while others have a higher level of readiness. Cluster analysis was used to group agencies by similarity in multiple dimensions. Strategies for increasing readiness are highlighted. This identifies opportunities for agencies and the WildFireSat team to collaborate on enhancing readiness for the forthcoming WildFireSat data products.

Byram’s fire intensity (IB,tot; kWm–1) is one the most important and widely accepted metrics for quantifying wildfire behaviour. Calculation of IB,tot requires measurement of fuel consumption, heat of combustion and rate of spread; existing methods for obtaining these measurements are either inexact or at times impossible to obtain in the field. This paper presents and evaluates a series of remote sensing methods for directly deriving radiative fire intensity (IB,rad; kWm–1) using the Fire Radiative Power (FRP) approach applied to thermal infrared imagery of spreading vegetation fires. Comparisons between the remote sensing data and ground-sampled measurements were used to evaluate the various estimates of IB,tot, and to determine the radiative fraction (radF) of a fire’s emitted energy. Results indicate that the IB,tot along an advancing flame front can be reasonably estimated (and agrees with traditional methods of estimation (R2=0.34–0.73)) from appropriately collected time-series of remote sensing imagery without the need for ground sampling or ancillary data. We further estimate that the radF of the fire’s emitted energy varies between 0.15 and 0.20 depending on the method of calculation, which is similar to previous estimates.

In recent years, time-critical processing or real-time processing and analytics of bid data have received a significant amount of attentions. There are many areas/domains where real-time processing of data and making timely decision can saves thousands of human lives, minimizing the risks of human lives and resources, enhance the quality of human lives, enhance the chance of profitability, efficient resources management etc. This paper have presented such type of real-time big data analytic applications and a classification of those applications. In addition it presents the time requirements of each type of these applications along with its significant benefits. Also, a general overview of big data to describe a background knowledge on this scope.

The temperature and emissivity of forest fire flames play a key role in understanding fire behaviour, modelling fire spread and calculating fire parameters by means of active fire thermal remote sensing. Essential to many of these is the often-made assumption that vegetation fire flames behave as grey bodies in the infrared (IR). Although the emissivity of flames and its relationship to flame depth has been measured experimentally using thermal imagers working in the long-wave IR (LWIR, 8-12 mu m), no published study has yet demonstrated relationships in the important mid-wave IR (MWIR, 3-5 mu m) spectral region, nor conclusively demonstrated that assumptions about grey body behaviour across these two important IR atmospheric windows fit well with reality. Our study explores these issues using measurements of boreal forest fuels burned with flame depths ranging from 0.2 to 4.2 m. Observations of two stable black body sources made through the differing flame depths were used to explore flame spectral emissivities and their relationship to flame depth. We found essentially the same relationship between flame emissivity and flame depth for both spectral regions, (extinction coefficient K = 0.7 m(-1)), confirming that the grey body assumption for forest fire flames in the MWIR and LWIR atmospheric windows appears valid for the fire conditions encountered here.

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.

To fully understand the carbon (C) cycle impacts of forest fires, both C emissions during the fire and post-disturbance fluxes need to be considered. The latter are dominated by soil surface CO2 flux (Fs), which is still subject to large uncertainties. Fire is generally regarded as the most important factor influencing succession in the boreal forest biome and fire dependant species such as jack pine are widespread. In May 2007, we took concurrent Fs and soil temperature (Ts) measurements in boreal jack pine fire scars aged between 0 and 59 years since fire. To allow comparisons between scars, we adjusted Fs for Ts (FsT) using a Q10 of 2. Mean FsT ranged from 0.56 (± 0.30 sd) to 1.94 (± 0.74 sd) μmol CO2 m−2 s−1. Our results indicate a difference in mean FsT between recently burned (4 to 8 days post fire) and non-burned mature (59 years since fire) forest (P < 0.001), though no difference was detected between recently burned (4 to 8 days post fire) and non-burned young (16 years since fire) forest (P = 0.785). There was a difference in mean FsT between previously young (16 years since fire) and intermediate aged (32 years since fire) scars that were both subject to fire in 2007 (P < 0.001). However, there was no difference in mean FsT between mature (59 years since fire) and intermediate aged (32 years since fire) scars that were both subjected to fire in 2007 (P = 0.226). Furthermore, there was no difference in mean FsT between mature (59 years since fire) and young scars (16 years since fire) that were both subjected to fire in 2007 (P = 0.186). There was an increase in FsT with time since fire for the chronosequence 0, 16 and 59 years post fire (P < 0.001). Our results lead us to hypothesise that the autotrophic:heterotrophic soil respiration ratio increases over post-fire successional time in boreal jack pine systems, though this should be explored in future research. The results of this study contribute to a better quantitative understanding of Fs in boreal jack pine fire scars and will facilitate meta-analyses of Fs in fire scar chronosequences.

Abstract. To fully understand the carbon (C) cycle impacts of forest fires, both C emissions during the fire and post-disturbance fluxes need to be considered. The latter are dominated by soil respiration (Rs), which is still subject to large uncertainties. This research investigates Rs in a boreal jack pine fire scar chronosequence at Sharpsand Creek, Ontario, Canada. During two field campaigns in 2006 and 2007, Rs was measured in a chronosequence of fire scars aged between 0 and 59 years since the last fire. Mean Rs per fire scar was adjusted for soil temperature (Ts) and soil moisture (Ms) (denoted RST,M). RST,M ranged from 0.56 μmol CO2/m2/s (32 years post fire) to 8.18 μmol CO2/m2/s (58 years post fire). The coefficient of variation (CV) of RST,M ranged from 20% (16 years post fire) to 56% (58 years post fire). Across the field site, there was a statistically highly significant exponential relationship between Rs adjusted for soil organic carbon (Cs) and Ts (P<0.00001; Q10=2.21) but no effect of Ms on Rs adjusted for Cs and Ts for the range 0.21 to 0.77 volumetric Ms (P=0.702). RST,M decreased significantly (P=0.030) after fire (4 to 8 days post fire) in mature forest, though no significant (P>0.1) difference could be detected between recently burned (4 to 8 days post fire) and unburned young forest. There were significant differences in RST,M between recently burned (4 to 8 days post fire) scar age categories that differed in their burn history, with between-fire intervals of 32 vs. 16 years (P<0.001) and 32 vs 59 years (P=0.044). There was a highly significant exponential increase in RST,M with time since fire (r2=0.999; P=0.006) for the chronosequence 0, 16 and 59 years post fire, and for all these age categories, RST,M was significantly different from one another (P<0.05). The results of this study contribute to a better quantitative understanding of Rs in boreal jack pine fire scars and will facilitate improvements in C cycle modelling. Further work is needed in quantifying autotrophic and heterotrophic contributions to Rs in jack pine systems; in monitoring Rs for extended time periods after fire; and in measuring different fire-prone forest types.

In many forest types, over half of the total stand biomass is located in the forest floor. Carbon emissions during wildland fire are directly related to biomass (fuel) consumption. Consumption of forest floor fuel varies widely and is the greatest source of uncertainty in estimating total carbon emissions during fire. We used experimental burn data (59 burns, four fuel types) and wildfire data (69 plots, four fuel types) to develop a model of forest floor fuel consumption and carbon emissions in nonpeatland standing-timber fuel types. The experimental burn and wildfire data sets were analyzed separately and combined by regression to provide fuel consumption models. Model variables differed among fuel types, but preburn fuel load, duff depth, bulk density, and Canadian Forest Fire Weather Index System components at the time of burning were common significant variables. The regression R-2 values ranged from 0.206 to 0.980 (P < 0.001). The log-log model for all data combined explained 79.5% of the regression variation and is now being used to estimate annual carbon emissions from wildland fire. Forest floor carbon content at the wildfires ranged from 40.9% to 53.9%, and the carbon emission rate ranged from 0.29 to 2.43 kg.m(-2).

The severity of a burn for post-fire ecological effects has been assessed with the composite burn index (CBI) and the differenced Normalized Burn Ratio (dNBR). This study assessed the relationship between these two variables across recently burned areas located in the western Canadian boreal, a region not extensively evaluated in previous studies. Of particular interest was to evaluate the nature of the CBI-dNBR relationship from the perspectives of modelling, the influence of fire behaviour prediction (FBP) fuel type, and how field observations could be incorporated into the burn severity mapping process. A non-linear model form best represented the relationship between these variables for the fires evaluated, and a similar statistical performance was achieved when data from all fires were pooled into a single dataset. Results from this study suggest the potential to develop a single model for application over the western region of the boreal, but further evaluation is necessary. This evaluation could include stratification by FBP fuel type due to study results that document its apparent influence on dNBR values. A new approach for burn severity mapping was introduced by defining severity thresholds through field assessment of CBI, and from which development of new models could be incorporated directly into the mapping process.

We studied an upland boreal forest plot located in the Prince Albert National Park, Saskatchewan, Canada, to measure the total mercury content in vegetation and organic soil with a view to assessing the potential for mercury release during forest fires. The study area consists of two stands of vegetation regrown after fires 39 and 130 years ago, with different carbon and mercury stocks in vegetation and organic soil. The mercury concentrations in ng g−1 (dry weight) were measured for moss (90–110), leaves (8), needles (10), bark (16–38), lichen (30–227), bole wood (2) and for organic soil layers (120–300). The combined mercury stock increased from 1.01 ± 0.28 to 3.45 ± 0.87 mg m−2 for the two stand ages; 93–97% of the mercury resided in the organic soil to the mineral layer. The mercury input to the ecosystem is from wet and dry deposition and is trapped in the organic soil layers as indicated by the high organic soil mercury concentrations and low mercury concentration in the underlying mineral layer. Extrapolation from the data measured for the two subplots to all boreal forests suggests a massive mercury stock in boreal forests (15,000 to 44,000 t). This is a low estimate because boreal lowlands have still higher mercury densities. Not all of the organic soil mercury was acquired since the last burns; some predates the more recent fires. The mercury being predominantly located in the organic soil makes fire severity the most important parameter for mercury release. The anticipated accelerated warming in northern latitudes would increase severity, frequency and burn area of future fires and result in large pulses of mercury to the atmosphere and further stress to the environment.

Satellite-based mapping can provide a timely and efficient means of identifying burned vegetation at continental scales for estimating greenhouse gas emissions and impacts on the terrestrial carbon budget. In this study, we used a sample of 55 Landsat Thematic Mapper (TM) scenes distributed across Canada to validate and calibrate 1998 and 1999 national­ level burned areas maps produced using coarse resolution (approx. 1-km) SPOT VEGETATION and NOAA AVHRR imagery. Commission and omissions errors, based on fire events greater than 200 ha, were found to be small in the coarse resolution maps (4 percent and 1 percent, respectively). However, the coarse resolution burned-area estimates were 72 percent larger than the crown fire burned area mapped at 30 musing Landsat TM (11,039 versus 6,403 ha average area). This bias was attributed to spatial aggregation effects in which the coarse resolution product included the tree crown fire, partial burn, and unburned fractions of a pixel. A regression calibra­ tion model (R2 = 0.95, P < 0.0005, RMSE = 3,015 ha, n = iSS) based on a VGT/TM double sampling approach was derived to correct for the aggregation bias and to provide Canada-wide estimates of crown fire burned area.

The Fire Monitoring, Mapping and Modelling System (Fire M3) is an initiative of the Canada Centre for Remote Sensing (CCRS) and the Canadian Forest Service (CFS), both agencies of Natural Resources Canada. The goals of Fire M3 are to use low-reso- lution satellite imagery to monitor actively burning fires on a daily basis; to estimate annual area burned; and to model fire behav- ior, biomass consumption, and carbon emissions from fires. Same-day fire products are made available on the Fire M3 web site and have been used for a variety of purposes including national reporting and climate change research. The daily operation of the system during the forest fire season involves 1) satellite image reception in Saskatchewan and Quebec; 2) production of geocod- ed, Canada-wide composite images at CCRS; 3) application of CCRS fire, smoke, and burned-area detection algorithms to pro- duce raw fire products; 4) production of final daily fire products at CFS, including weather-based fire behavior modeling; and 5) dissemination of daily fire products on the Fire M3 web site within 12 hours of satellite reception.

The Wildland Fire Hazard Team reviewed potential requirements for space-based observations in fire management. The team produced a report, developed under the auspices of the Disaster Management Support Group (DMSG) of the G-7 Committee on Earth Observation Satellites (CEOS). The document was prepared by an international working group, with experience in the field of remote sensing as applied to wildland fire management. The team identified seven major requirements. (http://disaster.ceos.org/2000Ceos/progress/reports/fire.html) These requirements could substantially improve wildland fire management programs, should CEOS augment existing satellites or develop new Earth observation satellites as recommended. The requirements address the different temporal, spatial, and spectral characteristics needed in different phases of fire management and geographic areas of interest. These requirements include fuel mapping, risk assessment, detection, monitoring, mapping, burned area recovery, and smoke management. They are supported by 10 recommendations, as outlined in this paper.

This paper provides an overview of four national forest fire management information systems currently used in Canada. The Canadian forest fire danger rating system (CFFDRS) is a non-spatial system, which provides the science framework for fire danger rating in Canada. The spatial fire management system (sFMS) is a geographic information system based fire management information system that implements two core subsystems of the CFFDRS, along with other models and systems. The sFMS is the spatial engine that has been used to implement both of Canada's national forest fire management information systems, the Canadian wildland fire information system (CWFIS) and the fire monitoring, mapping and modeling system (Fire M3). The CWFIS is Canada's national fire management information system; it presents daily information on fire weather, fire behavior potential and selected upper atmospheric conditions. Fire M3 integrates the use of satellite technology for monitoring and mapping large fire occurrence in Canada. Fire M3 also incorporates information from CWFIS to model the impacts of large forest fires based on fire weather conditions and potential fire behavior.