Airborne forest fire mapping with an adaptive infrared sensor

Oertel, D.; Brieß, K.; Halle, Winfried; Neidhardt, Michael; Lorenz, Eckehard; Sandau, Rainer; Schrandt, Friedrich; Skrbek, W.; Venus, Holger; Walter, Ingo; Zender, Bernd; Zhukov, B.; Goldammer, J. G.; Held, Alexander C.; Hille, M.G.; Brueggemann, H.

doi:10.1080/0143116021000033267

Cited by 9 publications

(4 citation statements)

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“…This can cause, for example, the radiant power contribution from a fire to vary between the spectral bands of the sensor, with the result that the fire may contribute proportionally more to the MIR band signal of a ‘fire’ pixel than to the TIR band for example (with the reverse likely in the neighbouring pixel). Such effects invalidate the bi‐spectral model's assumption that the fire fractional area is consistent across the MIR and TIR spectral bands of the fire pixel, and thus perturb the retrieval of fire fractional area and temperature [ Oertel et al , 2003; Zhukov et al , 2005a, 2005b]. However, careful application of the bi‐spectral approach can mitigate the consequences of interchannel spatial misregistration and PSF differences, generally by analysing the cumulative signal of clusters of spatially contiguous fire pixels rather than the individual fire pixels themselves [ Zhukov et al , 2005b].…”

Section: Remote Sensing Fire Radiative Powermentioning

confidence: 99%

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

et al. 2005

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[1] Estimates of wildfire aerosol and trace gas emissions are most commonly derived from assessments of biomass combusted. The radiative component of the energy liberated by burning fuel can be measured by remote sensing, and spaceborne fire radiative energy (FRE) measures can potentially provide detailed information on the amount and rate of biomass consumption over large areas. To implement the approach, spaceborne sensors must be able to derive fire radiative power (FRP) estimates from subpixel fires using observations in just one or two spectral channels, and calibration relationships between radiated energy and fuel consumption must be developed and validated. This paper presents results from a sensitivity analysis and from experimental fires conducted to investigate these issues. Within their methodological limits, the experimental work shows that FRP assessments made via independent hyperspectral and MIR radiance approaches in fact show good agreement, and fires are calculated to radiate 14 ± 3% [mean ± 1S.D.] of their theoretically available heat yield in a form capable of direct assessment by a nadir-viewing MIR imager. The relationship between FRE and fuel mass combusted is linear and highly significant (r 2 = 0.98, n = 29, p < 0.0001), and FRP is well related to combustion rate (r 2 = 0.90, n = 178, p < 0.0001), though radiation from the still-hot fuel bed can sometimes contribute significant FRP from areas where combustion has ceased. We conclude that FRE assessment offers a powerful tool for supplementing existing burned-area based fuel consumption measures, and thus shows significant promise for enhancing pyrogenic trace gas and aerosol emissions estimates.Citation: Wooster, M. J., G. Roberts, G. L. W. Perry, and Y. J. Kaufman (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,

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Section: Remote Sensing Fire Radiative Powermentioning

confidence: 99%

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

et al. 2005

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“…Airborne sensors have also been used extensively in support of fire management in the United States, and to a lesser extent in support of fire science studies in different geographic regions (Kaufman, Kleidman, & King, 1998;King, Platnick, Moeller, Revercomb, & Chu, 2003;Oertel et al, 2003;Riggan et al, 2004). Use of airborne platforms for quantitative fire imaging requires that sensors operating in the middle-infrared (≈4 μm) spectral region have a high dynamic range because it is in this region that fires emit most of their radiation.…”

Section: Introductionmentioning

confidence: 99%

Integrated active fire retrievals and biomass burning emissions using complementary near-coincident ground, airborne and spaceborne sensor data

Schroeder

Ellicott

Ichoku

et al. 2014

Remote Sensing of Environment

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Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed nearcoincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing highquality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (b 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5% difference between Aqua/MODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg MJ −1 , total energy release of 14.5e + 06 MJ, and total fuel consumption of 3.8e + 06 kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15% difference for various species.

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“…The methodology has proven to provide successfully monitoring results over 2000 km 2 in Central Italy (Lazio) allowing to map forest burnt areas with an accuracy compatible with 1:10000 scale level. Remote sensing by aerial light vectors can be effi ciently (in terms of imagery quality and cost) used to map and qualify with high accuracy damages on distinctive spots, and it is also particularly suitable for calibrating remotely sensed imagery of lower geometric resolu tion (Oertel et al 2003).…”

Section: Aerial Assessment: the Simib Projectmentioning

confidence: 99%