1 Spatial Modelling of the Terrestrial Environment - Georeferencial

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Fireline Intensity and Biomass Consumption in Wildland Fires 191 Figure 9.7 FRE derived for the first two GOES pixels identified as being affected by the 1996 Miller’s Reach Fire (Alaska), shown here between 19:40, 3 June and 01:25, 4 June. The fire reportedly decreased very rapidly in size and intensity within 1:30 hr after 01:00 on 4 June (Hufford et al., 2000) fire, and estimation of their exact combination is not simple and remains an important research goal (Thomas, 1971; Weber, 1991). Nevertheless, this example does indicate the feasibility of making FRE measurements from geostationary orbit and, if the relationship between FRE and biomass consumption can be accurately characterized, of relating these observations to biomass volatized and emissions produced. 9.5 Potential Use of Fire Radiative Energy in Fire Propagation Modelling In addition to their potential use in estimating the mass of combusted vegetation and the resultant pollutant emissions, remotely sensed measures of wildfire heat output may hold significant value for modelling the spatial propagation of wildfires. For such modelling of fire dynamics, local measures of the rate of heat generation are usually more important
192 Spatial Modelling of the Terrestrial Environment than the total heat output rate of the fire. Thus, although the rate of heat generated per unit length of the fire front (i.e., the fireline intensity) is a parameter commonly used to describe wildfire, Anderson (1969) and Rothermel (1972) found that the heat generated per unit area (known as the combustion rate) is both less variable and more useful in the prediction of the rate of spread in surface fires. Another related measure is the reaction intensity, which also describes the heat release per unit area of ground beneath the fuel bed. The reaction intensity curve describes the consumption of the fuel as the fire burns down and through the fuel bed over some fixed point on the ground (Cheney, 1990). In some cases a third measure of intensity, the total heat output, is the most appropriate measure, being most useful in the prediction and correlation of convection plume phenomena such as spotting which can significantly increase the rate of fire spread. A final intensity parameter is convective intensity, defined as that portion of the total heat output used to lift the resultant pollutant products and entrained air above the flame zone, and calculated by subtracting the estimated conductive and radiative heat losses from the total energy release rate (Chandler et al., 1983). To predict or estimate any of these measures of fire intensity, vegetation has had to be classified into burnt and unburnt components. Living plant matter may or may not burn in a surface fire because its FMC can lie between 80 and 200% (Pyne, 1984). By contrast, dead plant matter components have a FMC fixed by recent atmospheric activity, below a fibre saturation of ∼30% (Rothermel, 1972; Albini, 1993). If the burning of dead plant matter creates a fire of sufficient intensity, then the smaller living plant components will also be burned and will contribute to the local heat release rate. In most cases, however, it is usually assumed that it is the dead fine fuels that carry most wildfires. As already discussed, however, the calculation and interpretation of fire intensity measures are often very difficult from measurements made in the field (and usually impossible for very severe events) and interpretation of these values has proved problematic (Alexander, 1982). The new remote sensing methodologies for directly measuring heat release rates we have presented provide a potential method of improving estimates of fire intensity and energy fluxes, particularly for the most difficult to measure large-scale fire events. Thus, this might not only enable improved estimation of particulate and chemical emissions, but also prove useful for the parameterization, development and improvement of a new generation of physically based fire behaviour models (see Perry, 1998). 9.6 Conclusion Clearly, research on FRE is at a fairly early stage and remotely sensed FRE estimates and any resultant estimate of biomass consumption must be rigorously analysed for their accuracy and representativeness, a process that began with the work of Kaufman et al. (1996) on airborne remote sensing but which is now beginning to be considered at the satellite scale. The methods now available from satellite-based sensors clearly offer a new approach to determining a measure of fireline intensity, traditionally a difficult-to-measure parameter, though the radiative-based measures available from IR remote sensing still need to be understood in the context of the wider heat-loss mechanisms operating. Recently, Sazanovich and Tsvyk (2002) have commenced attempts to determine the relative partitioning between the heat loss processes of radiation, convection and conduction more precisely, initially
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Spatial Modelling of the Terrestria
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Copyright C○ 2004 John Wiley & So
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Contents List of Contributors Prefa
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Contributors Jonathan L. Bamber Sch
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List of Contributors xi George Perr
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xiv Preface in theory and applicati
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2 Spatial Modelling of the Terrestr
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Editorial: Spatial Modelling in Hyd
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Editorial: Spatial Modelling in Hyd
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2 Modelling Ice Sheet Dynamics with
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Modelling Ice Sheet Dynamics by Sat
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36 Spatial Modelling of the Terrest
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4 Using Coupled Land Surface and Mi
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Coupled Land Surface and Microwave
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100 Spatial Modelling of the Terres
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Editorial: Terrestrial Sediment and
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Editorial: Terrestrial Sediment and
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6 Remotely Sensed Topographic Data
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Remotely Sensed Topographic Data fo
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7 Modelling Wind Erosion and Dust E
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Modelling Wind Erosion and Dust Emi
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PART IV CURRENT CHALLENGES AND FUTU
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268 Index Bi-spectral InfraRed Dete
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270 Index floodplain maps, UK 92 fl
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272 Index Long-Term Ecological Rese
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274 Index snow depth measurement ne
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276 Index urban land use in remotel
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1 Spatial Modelling of the Terrestrial Environment - Georeferencial

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