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

Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+ data

David L. Verbyla A C , Eric S. Kasischke B and Elizabeth E. Hoy B
+ Author Affiliations
- Author Affiliations

A Department of Forest Sciences, University of Alaska, Fairbanks, AK 99775, USA.

B Department of Geography, University of Maryland, 2181 LeFrak Hall, College Park, MD 20742, USA.

C Corresponding author. Email:

International Journal of Wildland Fire 17(4) 527-534
Submitted: 4 March 2008  Accepted: 16 June 2008   Published: 6 August 2008


The maximum solar elevation is typically less than 50 degrees in the Alaskan boreal region and solar elevation varies substantially during the growing season. Because of the relatively low solar elevation at boreal latitudes, the effect of topography on spectral reflectance can influence fire severity indices derived from remotely sensed data. We used Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data to test the effect of changing solar elevation and topography on the Normalized Burn Ratio (NBR) and the differenced Normalized Burn Ratio (dNBR). When a time series of unburned pixels from black spruce forests was examined, we found that NBR values consistently decreased from June through September. At the stand level, dNBR-derived values from similar unburned and burned black spruce stands were substantially higher from September imagery relative to July or August imagery. Within the Boundary burn, we found mean post-fire NBR to consistently vary owing to topographic control of potential solar radiation. To minimise spectral response due to topographic control of vegetation and fire severity, we computed a dNBR using images from August and September immediately after a June–July wildfire. There was a negative bias in remotely sensed fire severity estimates as potential solar radiation decreased owing to topography. Thus fire severity would be underestimated for stands in valley bottoms dominated by topographic shading or on steep north-facing slopes oriented away from incoming solar radiation. This is especially important because highly flammable black spruce stands typically occur on such sites. We demonstrate the effect of changing pre- and post-fire image dates on fire severity estimates by using a fixed NBR threshold defining ‘high severity’. The actual fire severity was constant, but owing to changes in phenology and solar elevation, ‘high severity’ pixels within a burn ranged from 56 to 76%. Because spectral reflectance values vary substantially as solar elevation and plant phenology change, the use of reflectance-based indices to assess trends in burn severity across regions or years may be especially difficult in high-latitude areas such as the Alaskan boreal forest.

Additional keywords: boreal forest, fire severity, Normalized Burn Ratio, solar elevation, topography.


Funding for the present project was provided by the Bonanza Creek Long-term Ecological Research Program (funded jointly by National Science Foundation grant DEB-0423442 and USDA Forest Service, Pacific Northwest Research Station grant PNW01-JV11261952–231), the Joint Fire Science Program, and by NASA through Grant number NNG05GD25G. Data from this research are archived and available through the Bonanza Creek Long Term Ecological Research (BNZ-LTER) website (, accessed 22 July 2008).


Bobbe T, Finco MV, Quayle B, Lannon K, Sohlberg R, Parsons A (2001) Field measurements for the training and validation of burn severity maps from spaceborne, remotely sensed imagery. USDA Forest Service, Remote Sensing Application Center, Joint Fire Science Report 2001–2. (Salt Lake City, UT)

Chander G , Markham B (2003) Revised Landsat-5 TM radiometric calibration procedures and post-calibration dynamic ranges. IEEE Transactions on Geoscience and Remote Sensing  41, 2674–2677.
CrossRef |

Civco DL (1989) Topographic normalization of Landsat Thematic Mapper digital imagery. Photogrammetric Engineering and Remote Sensing  55, 1303–1309.

Ekstrand S (1996) Landsat-TM based forest damage assessment: correction for topographic effects. Photogrammetric Engineering and Remote Sensing  62, 151–161.

Epting J, Verbyla D , Sorbel B (2005) Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM+. Remote Sensing of Environment  96, 328–339.
CrossRef |

Fu P , Rich PM (2002) A geometric solar radiation model with applications in agriculture and forestry. Computers and Electronics in Agriculture  37, 25–35.
CrossRef |

Holben B , Justice C (1981) An examination of spectral band ratioing to reduce the topographic effect on remotely sensed data. International Journal of Remote Sensing  2, 115–133.
CrossRef |

Howard SM , Lacasse JM (2004) An evaluation of gap-filled Landsat SLC-Off imagery for wildland fire burn severity mapping. Photogrammetric Engineering and Remote Sensing  70, 877–880.

Hoy EE, French NHF, Turetsky MR, Trigg SN , Kasischke ES (2008) Evaluating the potential of Landsat TM/ETM+ imagery for assessing fire severity in Alaskan black spruce forests. International Journal of Wildland Fire  17, 500–514.
CrossRef |

Isaev AS, Korovin GN, Bartalev SA, Ershov DV, Janetos A, Kasischke ES, Shugart HH, French NH, Orlick BE , Murphy TL (2002) Using remote sensing to assess Russian forest fire carbon emissions. Climatic Change  55, 235–249.
CrossRef |

Kane ES, Kasischke ES, Valentine DW, Turetsky MR , McGuire AD (2007) Topographic influences on wildfire consumption of soil organic carbon in black spruce forests of interior Alaska: implications for black carbon accumulation. Journal of Geophysical Research  112, G03017.
CrossRef |

Kasischke ES , French NHF (1997) Constraints on using AVHRR composite index imagery to study patterns of vegetation cover in boreal forests. International Journal of Remote Sensing  18, 2403–2426.
CrossRef |

Kasischke ES, Turetsky MR, Ottmar RD, French NHF, Hoy EE , Kane ES (2008) Evaluation of the composite burn index for assessing fire severity in Alaskan black spruce forests. International Journal of Wildland Fire  17, 515–526.
CrossRef |

Key CH, Benson NC (2006) Landscape assessment: ground measure of severity, the Composite Burn Index, and remote sensing of severity, the Normalized Burn Index. In ‘FIREMON: Fire Effects Monitoring and Inventory System’. (Eds DC Lutes, RE Keane, JF Caratti, CH Key, NC Benson, S Sutherland, LJ Gangi) USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-164-CD: LA1–51. (Ogden, UT)

Kotliar NB, Haire SL, Key CH (2003) Lessons from the fires of 2000: post-fire heterogeneity in Ponderosa pine forests. In ‘Fire, Fuel Treatments, and Ecological Restoration: Conference Proceedings’, 16–18 April 2002, Fort Collins, CO. (Tech. Eds PN Omi, LA Joyce) USDA Forest Service, Rocky Mountain Research Station, Proceedings RMRS-P-29, pp. 277–280. (Fort Collins, CO)

Landmann T (2003) Charcterizing sub-pixel Landsat ETM+ fire severity on experimental fires in the Kruger National Park, South Africa. South African Journal of Science  99, 357–360.

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.
CrossRef |

NASA Goddard Space Flight Center (2003) ‘Landsat 7 Science Data Users Handbook.’ (Landsat Project Science Office: Greenbelt, MD) Accessed at [Verified 23 July 2008]

Patterson MW , Yool SR (1998) Mapping fire-induced vegetation mortality using Landsat Thematic Mapper data: a comparison of linear transformation techniques. Remote Sensing of Environment  65, 132–142.
CrossRef |

Riano D, Chuvieco E, Salas J , Aguado I (2003) Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types. IEEE Transactions on Geoscience and Remote Sensing  41, 1056–1061.
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.
CrossRef |

Short NM (1982) ‘The Landsat Tutorial Workbook: Basics of Satellite Remote Sensing.’ (NASA Scientific and Technical Information Branch: Washington, DC)

Trigg S , Flasse S (2000) Characterizing the spectral-temporal response of burned savannah using in situ spectroradiometry and infrared thermometry. International Journal of Remote Sensing  21((16)), 3161–3168.
CrossRef |

van Wagtendonk JW, Root RR , Key C (2004) Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity. Remote Sensing of Environment  92, 397–408.
CrossRef |

White JD, Ryan K, Key CC , Running SW (1996) Remote sensing of forest fire severity and vegetation recovery. International Journal of Wildland Fire  6, 125–136.
CrossRef |

Export Citation Cited By (56)