Forest fuel mapping and evaluation of LANDFIRE fuel maps in Boulder County, Colorado, USA

Krasnow, Kevin D.; Schoennagel, Tania; Veblen, Thomas T.

doi:10.1016/j.foreco.2009.01.020

Cited by 56 publications

(42 citation statements)

References 33 publications

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“…This method results in less distortion of fire shape and response to temporally varying conditions than techniques that model fire growth from cell-tocell on a gridded landscape (Finney, 2002). Extensive testing over the years has demonstrated that the Huygens' principle as originally incorporated into Farsite (Finney, 1998) and later approximated in the more efficient MTT algorithm can accurately predict fire spread and replicate large fire boundaries on heterogeneous landscapes (Sanderlin and Van Gelder, 1977;Anderson et al, 1982;Knight and Coleman, 1993;Finney, 1994;Miller and Yool, 2002;LaCroix et al, 2006;Ager et al, 2007a;Arca et al, 2007;Krasnow et al, 2009;Carmel et al, 2009;Massada et al, 2009). The MTT algorithm in Randig is multi-threaded (computations for a given fire are performed on multiple processors), making it feasible to perform Monte Carlo simulations of many fires (>50,000) to generate burn probability surfaces for very large (>2 million ha) landscapes (Ager and Finney, 2009).…”

Section: Wildfire Simulationsmentioning

confidence: 99%

A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure

Ager

Vaillant

Finney

2010

Forest Ecology and Management

264

203

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Section: Wildfire Simulationsmentioning

confidence: 99%

A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure

Ager

Vaillant

Finney

2010

Forest Ecology and Management

264

203

View full text Add to dashboard Cite

“…This method results in less distortion of fire shape and response to temporally varying conditions than techniques that simulate fire growth from cell-to-cell on a gridded landscape (Finney, 2002). Extensive testing over the years has demonstrated that the Huygens' principle, originally incorporated into Farsite (Finney, 1998) and later approximated in the more efficient MTT algorithm, can accurately predict fire spread and replicate large fire boundaries on heterogeneous landscapes (Sanderlin and Van Gelder, 1977;Anderson et al, 1982;Knight and Coleman, 1993;Finney, 1994;Miller and Yool, 2002;LaCroix et al, 2006;Ager et al, 2007Ager et al, , 2010Arca et al, 2007;Krasnow et al, 2009;Carmel et al, 2009;Massada, 2009). The MTT algorithm in Randig is multithreaded (computations for a given fire are performed on multiple processors), making it feasible to perform Monte Carlo simulations of many fires (>50 000) to generate burn probability surfaces for very large (>2 million ha) landscapes (Ager and Finney, 2009).…”

Section: Wildfire Simulationsmentioning

confidence: 99%

Measuring the effect of fuel treatments on forest carbon using landscape risk analysis

Ager

Finney

McMahan

et al. 2010

Nat. Hazards Earth Syst. Sci.

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Abstract. Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscape scale effects of fuel treatments on fire spread and intensity, and used a probabilistic framework to quantify wildfire effects on carbon pools to account for stochastic wildfire occurrence. The study area was a 68 474 ha watershed located on the Fremont-Winema National Forest in southeastern Oregon, USA. Fuel reduction treatments were simulated on 10% of the watershed (19% of federal forestland). We simulated 30 000 wildfires with random ignition locations under both treated and untreated landscapes to estimate the change in burn probability by flame length class resulting from the treatments. Carbon loss functions were then calculated with the Forest Vegetation Simulator for each stand in the study area to quantify change in carbon as a function of flame length. We then calculated the expected change in carbon from a random ignition and wildfire as the sum of the product of the carbon loss and the burn probabilities by flame length class. The expected carbon difference between the nontreatment and treatment scenarios was then calculated to quantify the effect of fuel treatments. Overall, the results show that the carbon loss from implementing fuel reduction treatments exceeded the expected carbon benefit associated with lowered burn probabilities and reduced fire severity on the treated landscape. Thus, fuel management activities Correspondence to: A. A. Ager (aager@fs.fed.us) resulted in an expected net loss of carbon immediately after treatment. However, the findings represent a point in time estimate (wildfire immediately after treatments), and a temporal analysis with a probabilistic framework used here is needed to model carbon dynamics over the life cycle of the fuel treatments. Of particular importance is the longterm balance between emissions from the decay of dead trees killed by fire and carbon sequestration by forest regeneration following wildfire.

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“…The rationale of the study is that spatial patterns, including the composition and configuration of forests in a landscape, dictate the fire susceptibility of forests. Burn severity also partly depends on the spatial pattern of forests with high or low fire susceptibility (Cumming, 2001;Krasnow et al, 2009;Pyne et al, 1996). Furthermore, certain aspects of all fuel treatments, forest management practices, and restoration efforts are related to the spatial patterns of forests.…”

mentioning

confidence: 99%

Relationship between landscape structure and burn severity at the landscape and class levels in Samchuck, South Korea

Lee

et al. 2009

Forest Ecology and Management

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Forest fuel mapping and evaluation of LANDFIRE fuel maps in Boulder County, Colorado, USA

Cited by 56 publications

References 33 publications

A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure

A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure

Measuring the effect of fuel treatments on forest carbon using landscape risk analysis

Relationship between landscape structure and burn severity at the landscape and class levels in Samchuck, South Korea

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