FOR 435/535: Remote Sensing for Fire Management. FOR 435: Remote Sensing for Fire Management. FOR 435: Thermal Properties of Fires

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1 FOR 435/535: Remote Sensing for Fire Management FOR 435: Remote Sensing for Fire Management 4. Active Fire Behavior Thermal Properties of Fires Field Measures Remote Sensing The amount of heat per unit area per unit time is called the heat flux or fire intensity. Typically, this value is reported in kw per meter. The process of combustion has distinct phases beginning with pre-ignition of the fuel followed by dehydration and pyrolysis. These are followed by a transition stage of ignition, which leads to flaming and smoldering combustion followed by extinction. Figure from 1

2 Heat transfer is the movement of heat energy. This movement occurs whenever there is a heat difference between media. There are three primary modes of heat transfer conduction, convection and radiation. In fires, we also have latent heats of vaporization and condensation arising from phase changes. Figure from m_phys.html The general form of the energy transfer equation is: Flux = constant * (Final Gradient State Initial Gradient State) Conductive Heat Flux = k/l * (Final Temperature Initial Temperature) Convective Heat Flux = h * (Final Temperature Initial Temperature) Radiation Heat Flux = εσ [Object T 4 - Background T 4 ] Conduction: An object transfers its kinetic energy (i.e. Heat) to another object by its molecules hitting the molecules (making them move around) of the colder object. Convection: The kinetic energy of objects are moved from one location to another by physically moving the objects. Wind Heated Burned Surface Temperature Gradient Hayman Fire Interim Report Radiation: The transfer of energy via electromagnetic waves (or photons) is the only way the energy can be transferred within a vacuum (i.e. in space between the sun and the Earth). The Stefan-Boltzman Law provides a measure of the maximum energy emitted: E = εσ T 4 [σ = 5.67 x 10-8 watts/m 2 /K 4 ] ε = emissivity, 0 <= ε <= 1, and is the efficiency that surface emits energy when compared to a black body 2

3 In fire remote sensing studies we make the assumption that the energy is apportioned into the conductive, radiative, and convective component at the same proportion regardless of the fuel loading. Making this assumption allows you to infer convective and conductive (i.e. difficult to measure) components through direct measurement of the radiative energy, which is easy to measure. The validity of this assumption needs further research Via this assumption we can infer the fuel consumed through measures of the radiative energy. If the heat of combustion, H, of fuels is known, then the fuel consumed within a pixel can be calculated by: In the equation: H can be calculated via using a bomb calorimeter FRE is the fire radiative energy released Fr is the fraction of the total energy release (per unit area) that is apportioned to radiation. Wooster, M.J., et al. (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release, JGR, 110, D24311, doi: /2005jd006318, To get at FRE we use properties of the Stefan-Boltzman Law. In wildland fires, the T 4 relationship within the law, ensures that the radiation from the hot fires (>900K) dominates over any cooler background emissions (Kremens et al 2010). The trick is that we need to calculate the brightness or radiant temperature, T. We can measure this by either using a full range (UV-TIR: microns) spectroradiometer OR through using two or more radiometers. The 2 (or more) detector method allows an estimation of the brightness or radiant temperature (T) via dual band thermometry. 3

4 To get at FRE we use properties of the Stefan-Boltzman Law. In wildland fires, the T 4 relationship within the law, ensures that the radiation from the hot fires (>900K) dominates over any cooler background emissions (Kremens et al 2010). Step 1. Integrate the Stefan-Boltzman equation over the 2 bands To get at FRE we use properties of the Stefan-Boltzman Law. In wildland fires, the T 4 relationship within the law, ensures that the radiation from the hot fires (>900K) dominates over any cooler background emissions (Kremens et al 2010). Step 2. Calculate the radiant (brightness temperature), T Step 3. Determine the emissivity. Large hot flames ~0.15, warm soils ~ 0.85 (Kremens et al 2010). Alternatively, the product of ea can be calculated: W ( T ) LWIR εa = n n C( T + T ) s C is a calibration parameter and Ts is the temperature of the sensor. To get at FRE we use properties of the Stefan-Boltzman Law. In wildland fires, the T 4 relationship within the law, ensures that the radiation from the hot fires (>900K) dominates over any cooler background emissions (Kremens et al 2010). Step 4. FRE is then calculated through the Stefan-Boltzman Law A f is the fraction of unit area (i.e. of a pixel) occupied by the fire 4

5 FOR 435: Field Measures Quantifying radiant energy released is also important for evaluating effectiveness of fire shelters (they are designed to reflect 95% of the radiant energy) FOR 435: Field Measures The system consists of the following components: Various sensor packages Low cost multi-purpose p data logger Simple 6.2 m tower to get down looking view and distance from fire FOR 435: Field Measures 5

6 FOR 435: Remote Sensing Measures - Aerial Time Elapsed: h:mm:ss- -0:00:00- -0:03:18- -0:06:02- -0:08:28- -0:11:14- -0:16:48- -0:19:57- -0:22:56- -0:26:08- -0:29:02- -0:32:22- -0:35:43- -0:39:13- -0:42:21- -0:45:56- -0:49:22- -0:52:42- -0:55:56- -1:03:11- -1:07:08- -1:10:24- -1:13:33- -1:17:27- -1:21:35- -1:26:18- -1:30:09- -1:33:55- -1:38:16- -1:42:21- Example: WASP-LT Tar Hollow DBNF, KY FOR 435: Remote Sensing Measures - Aerial 12 Data From Kremens: WASP Arch Rock, OH Time integral (total energy) of 13 frames FRE fuel consumption based on 40 experimental plots Fuel Consumption vs. Total Radiant Enegy Release (FRE) 10 y = x y = x 8 FRE, MJ/m VF Data Wooster Linear (VF Data) Linear (Wooster) Fuel Consumed, kg/m 2 6

7 FOR 435: Remote Sensing Measures - Aerial FOR 435: Remote Sensing Measures - Aerial FOR 435: Remote Sensing Measures - Satellite MSG SEVIRI MIR channel TIR channel MIR-TIR Fire Map 15 mins imaging frequency 7

8 MODIS 3.9 μm channel images BIR MODIS and BIRD FRP data in Boreal Forest MODIS false alarms FRP data BIRD Zhukov, B., et al. (2005) Spaceborne detection and characterization of fires during the Bi-spectral Infrared Detection (BIRD) experimental small satellite mission ( ) Remote Sensing of Environment, 100, FOR 435: Remote Sensing Measures - Satellite Day of Burn FOR 435: Remote Sensing Measures - Satellite Roberts, G., et al. (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: Application to southern Africa using geostationary SEVIRI Imagery, JGR, 110, D21111, doi: /2005JD

9 FOR 435: Remote Sensing Measures - Satellite Biomass = 3.2 million tonnes (1.5 Mtonnes C) Combusted ( million tonnes adj. for cloud) Cloud effe ect Roberts, G., et al. (2005) Retrieval of biomass combustion rates and totals from fire radiative power observations: Application to southern Africa using geostationary SEVIRI Imagery, JGR, 110, D21111, doi: /2005JD FOR 435: Remote Sensing Measures - Satellite Head and Backing Grassland Fires Smith AMS, Wooster MJ (2005) Remote classification of head and backfire types from MODIS fire radiative power observations. International Journal of Wildland Fire 14, FOR 435: Remote Sensing Measures - Satellite Field Image 9

10 FOR 435: Remote Sensing Measures - Satellite Crown and Surface Boreal Forest Fires Wooster M.J, Zhang YH (2004) Boreal forest fires burn less intensely in Russia than in North America. Geophysical Research Letters 31, L doi: /2004gl Byram s Fire Intensity equation contains about as much information about a fire s behavior as can be crammed into one number. Van Wagner (1977) 10