International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Limitations and utilisation of Monitoring Trends in Burn Severity products for assessing wildfire severity in the USA

Crystal A. Kolden A B , Alistair M. S. Smith A and John T. Abatzoglou A
+ Author Affiliations
- Author Affiliations

A University of Idaho, 875 Perimeter Drive, MS3021, Moscow, ID 83844-3021, USA.

B Corresponding author. Email: ckolden@uidaho.edu

International Journal of Wildland Fire 24(7) 1023-1028 https://doi.org/10.1071/WF15082
Submitted: 9 April 2015  Accepted: 28 July 2015   Published: 14 September 2015

Abstract

The Monitoring Trends in Burn Severity project is a comprehensive fire atlas for the United States that includes perimeters and severity data for all fires greater than a particular size (~400 ha in the western US, and ~200 ha in the eastern US). Although the database was derived for management purposes, the scientific community has expressed interest in its research capacity. As with any derived data, it is critical to understand inherent limitations to maximise the utility of the dataset without compromising the inferences. The classified severity product in particular is of limited use to research due to a lack of both consistency in developing class thresholds and empirical relationships with ecological metrics. Here we review the products available and their development process, and characterise and quantify the limitations of the classified burn severity data product based on the use of highly variable and subjective classification thresholds. We suggest a framework for overcoming these limitations by developing a more robust classified product that will support ecological management and applications. This framework utilises field data to develop consistent, ecologically based thresholds that incorporate existing ecoregion classifications from LANDFIRE or other fire management frameworks already widely integrated into planning efforts.

Additional keywords: dNBR, Landsat, MTBS, RdNBR.


References

Abatzoglou JT, Kolden CA (2013) Relationships between climate and macroscale area burned in the western United States. International Journal of Wildland Fire 22, 1003–1020.
Relationships between climate and macroscale area burned in the western United States.CrossRef |

Bechtold WA, Patterson PL (Eds) (2005) The enhanced forest inventory and analysis program: national sampling design and estimation procedures. USDA Forest Service, Southern Research Station, General Technical Report SRS-GTR-80. (Ashville, NC)

Cansler CA, McKenzie D (2012) How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-sensing methods. Remote Sensing 4, 456–483.
How robust are burn severity indices when applied in a new region? Evaluation of alternate field-based and remote-sensing methods.CrossRef |

Cansler CA, McKenzie D (2014) Climate, fire size, and biophysical setting control fire severity and spatial pattern in the northern Cascade Range, USA. Ecological Applications 24, 1037–1056.
Climate, fire size, and biophysical setting control fire severity and spatial pattern in the northern Cascade Range, USA.CrossRef | 25154095PubMed |

De Santis A, Chuvieco E (2009) GeoCBI: a modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data. Remote Sensing of Environment 113, 554–562.
GeoCBI: a modified version of the Composite Burn Index for the initial assessment of the short-term burn severity from remotely sensed data.CrossRef |

Eidenshink J, Schwind B, Brewer K, Zhu Z, Quayle B, Howard S (2007) A project for monitoring trends in burn severity. Fire Ecology 3, 3–21.
A project for monitoring trends in burn severity.CrossRef |

French NH, Kasischke ES, Hall RJ, Murphy KA, Verbyla DL, Hoy EE, Allen JL (2008) Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results. International Journal of Wildland Fire 17, 443–462.
Using Landsat data to assess fire and burn severity in the North American boreal forest region: an overview and summary of results.CrossRef |

Hicke JA, Meddens AJH, Allen CD, Kolden CA (2013) Carbon stocks of trees killed by bark beetles and wildfire in the western United States. Environmental Research Letters 8, 035032
Carbon stocks of trees killed by bark beetles and wildfire in the western United States.CrossRef |

Holden ZA, Morgan P, Evans JS (2009) A predictive model of burn severity based on 20-year satellite-inferred burn severity data in a large southwestern US wilderness area. Forest Ecology and Management 258, 2399–2406.
A predictive model of burn severity based on 20-year satellite-inferred burn severity data in a large southwestern US wilderness area.CrossRef |

Hudak AT, Morgan P, Bobbitt MJ, Smith AMS, Lewis SA, Lentile LB, Robichaud PR, Clark JT, McKinley RA (2007) The relationship of multispectral satellite imagery to immediate fire effects. Fire Ecology 3, 64–90.
The relationship of multispectral satellite imagery to immediate fire effects.CrossRef |

Keane RE, Holsinger LM, Pratt SD (2006) Simulating historical landscape dynamics using the landscape fire succession model LANDSUM version 4.0. .USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-171CD. (Fort Collins, CO)

Key CH (2006) Ecological and sampling constraints on defining landscape fire severity. Fire Ecology 2, 34–59.
Ecological and sampling constraints on defining landscape fire severity.CrossRef |

Key CH, Benson NC (2006) Landscape assessment: sampling and analysis methods. USDA Forest Service, Rocky Mountain Research Station General Technical Report RMRS-GTR-164-CD. (Ogden, UT)

Kolden CA, Abatzoglou JT (2012) Wildfire consumption and interannual impacts by land cover in Alaskan boreal forest. Fire Ecology 7, 98–114.
Wildfire consumption and interannual impacts by land cover in Alaskan boreal forest.CrossRef |

Kolden CA, Rogan J (2013) Mapping wildfire burn severity in the Arctic tundra: novel approaches for an extreme environment. Arctic, Antarctic, and Alpine Research 45, 64–76.
Mapping wildfire burn severity in the Arctic tundra: novel approaches for an extreme environment.CrossRef |

Kolden CA, Weisberg PW (2007) Assessing accuracy of manually-mapped wildfire perimeters in topographically dissected areas. Fire Ecology 3, 22–31.
Assessing accuracy of manually-mapped wildfire perimeters in topographically dissected areas.CrossRef |

Kolden CA, Lutz JA, Key CH, Kane JT, Van Wagtendonk JW (2012) Mapped versus actual burned area within wildfire perimeters: characterizing the unburned. Forest Ecology and Management 286, 38–47.
Mapped versus actual burned area within wildfire perimeters: characterizing the unburned.CrossRef |

Lannom KO, Tinkham WT, Smith AMS, Abatzoglou JT, Newingham BA, Hall TE, Morgan P, Strand EK, Paveglio TB, Anderson JW, Sparks AM (2014) Defining extreme wildland fires using geospatial and ancillary metrics. International Journal of Wildland Fire 23, 322–337.
Defining extreme wildland fires using geospatial and ancillary metrics.CrossRef |

Lentile LB, Holden ZA, Smith AMS, Falkowski MJ, Hudak AT, Morgan P, Lewis SA, Gessler PE, Benson NC (2006a) Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire 15, 319–345.
Remote sensing techniques to assess active fire characteristics and post-fire effects.CrossRef |

Lentile LB, Smith FW, Shepperd WD (2006b) Influence of topography and forest structures on patterns of mixed severity fire in ponderosa pine forests of the South Dakota Black Hills, USA. International Journal of Wildland Fire 15, 557–566.
Influence of topography and forest structures on patterns of mixed severity fire in ponderosa pine forests of the South Dakota Black Hills, USA.CrossRef |

Lentile LB, Smith AMS, Hudak AT, Morgan P, Bobbitt MJ, Lewis SA, Robichaud PR (2009) Remote sensing for prediction of 1-year post-fire ecosystem condition. International Journal of Wildland Fire 18, 594–608.
Remote sensing for prediction of 1-year post-fire ecosystem condition.CrossRef |

Miller JD, Safford HD (2012) Trends in wildfire severity: 1984 to 2010 in the Sierra Nevada, Modoc Plateau, and southern Cascades, California, USA. Fire Ecology 8, 41–57.
Trends in wildfire severity: 1984 to 2010 in the Sierra Nevada, Modoc Plateau, and southern Cascades, California, USA.CrossRef |

Miller JD, Thode AE (2007) Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment 109, 66–80.
Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR).CrossRef |

Miller JD, Safford HD, Crimmins M, Thode AE (2009) Quantitative evidence for increasing forest fire severity in the Sierra Nevada and Southern Cascade Mountains, California and Nevada, USA. Ecosystems 12, 16–32.
Quantitative evidence for increasing forest fire severity in the Sierra Nevada and Southern Cascade Mountains, California and Nevada, USA.CrossRef |

Morrison KD, Kolden CA (2015) Modeling the impacts of wildfire on runoff and pollutant transport from coastal watersheds to the nearshore environment. Journal of Environmental Management 151, 113–123.
Modeling the impacts of wildfire on runoff and pollutant transport from coastal watersheds to the nearshore environment.CrossRef | 25549866PubMed |

Nelson KJ, Connot J, Peterson B, Martin C (2013) The LANDFIRE refresh strategy: updating the national dataset. Fire Ecology 9, 80–101.
The LANDFIRE refresh strategy: updating the national dataset.CrossRef |

Robichaud PR, Lewis SA, Laes DYM, Hudak AT, Kokaly RF, Zamudio JA (2007) Postfire soil burn severity mapping with hyperspectral image unmixing. Remote Sensing of Environment 108, 467–480.
Postfire soil burn severity mapping with hyperspectral image unmixing.CrossRef |

Rollins MG (2009) LANDFIRE: a nationally consistent vegetation, wildland fire, and fuel assessment. International Journal of Wildland Fire 18, 235–249.
LANDFIRE: a nationally consistent vegetation, wildland fire, and fuel assessment.CrossRef |

Roy DP, Boschetti L, Trigg SN (2006) Remote sensing of fire severity: assessing the performance of the normalized burn ratio IEEE Geoscience and Remote Sensing Letters 3, 112–116.
Remote sensing of fire severity: assessing the performance of the normalized burn ratioCrossRef |

Ryan KC, Opperman TS (2013) LANDFIRE – A national vegetation/fuels data base for use in fuels treatment, restoration, and suppression planning. Forest Ecology and Management 294, 208–216.
LANDFIRE – A national vegetation/fuels data base for use in fuels treatment, restoration, and suppression planning.CrossRef |

Smith AMS, Lentile LB, Hudak AT, Morgan P (2007) Evaluation of linear spectral unmixing and dNBR for predicting post-fire recovery in a N. American ponderosa pine forest. International Journal of Remote Sensing 28, 5159–5166.
Evaluation of linear spectral unmixing and dNBR for predicting post-fire recovery in a N. American ponderosa pine forest.CrossRef |

Smith AMS, Kolden CA, Tinkham WT, Talhelm A, Marshall JD, Hudak AT, Boschetti L, Falkowski MJ, Greenberg JA, Anderson JW, Kliskey A, Alessa L, Keefe RF, Gosz J (2014) Remote sensing the vulnerability of vegetation in natural terrestrial ecosystems. Remote Sensing of Environment 154, 322–337.
Remote sensing the vulnerability of vegetation in natural terrestrial ecosystems.CrossRef |

Sparks AM, Boschetti L, Smith AMS, Tinkham WT, Lannom KO, Newingham BA (2015) An accuracy assessment of the MTBS burned area product for shrub–steppe fires in the northern Great Basin, United States. International Journal of Wildland Fire 24, 70–78.
An accuracy assessment of the MTBS burned area product for shrub–steppe fires in the northern Great Basin, United States.CrossRef |

Wimberly MC, Cochrane MA, Baer AD, Pabst K (2009) Assessing fuel treatment effectiveness using satellite imagery and spatial statistics. Ecological Applications 19, 1377–1384.
Assessing fuel treatment effectiveness using satellite imagery and spatial statistics.CrossRef | 19769087PubMed |



Export Citation Cited By (4)

View Altmetrics