References for the developmental background and evaluation of
NBR/dNBR as a severity index
Allen, J.L. & Sorbel, B. (2008). Assessing the differenced Normalized Burn Ratio's ability to map burn severity in the boreal forest and tundra ecosystems of Alaska's national parks. International Journal of Wildland Fire 17, 463–475.
Barrett, K., Kasischke, E.S., McGuire, A.D., Turetsky, M.R., Kane, E.S. (2010). Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data. Remote Sensing of Environment, 114 (7), 1494-1503.
Boer, M.M., Macfarlane, C., Norris, J., Sadler, R.J., Wallace, J. & Grierson, P.F. (2008). Mapping burned areas and burn severity patterns in SW Australian eucalypt forest using remotely-sensed changes in leaf area index. Remote Sensing of Environment, 112(12), 4358-4369.
Brewer, K.C., Winne, J.C., Redmond, R.L., Opitz, D.W. & Mangrich, M.V. (2005). Classifying and mapping wildfire severity: A comparison of methods. Photogrammetric Engineering and Remote Sensing, 71(11), 1311-1320.
Cocke, A.E., Fulé, P.Z. & Crouse, J.E. (2005). Comparison of burn severity assessments using Differenced Normalized Burn Ratio and ground data. International Journal of Wildland Fire, 14, 189-198.
De Santis, A. & Chuvieco, E. (2007). Burn severity estimation from remotely sensed data: Performance of simulation versus empirical models. Remote Sensing of Environment, 108(4), 422-435.
De Santis, Angela, Asner, Gregory P., Vaughan, Patrick J., Knapp, David E. (2010). Mapping burn severity and burning efficiency in California using simulation models and Landsat imagery. Remote Sensing of Environment, 114 (7), 1535-1545.
Duffy, P.A., Epting, J,, Graham, J.M., Rupp, T.S. & McGuire, A.D. (2007). Analysis of Alaskan burn severity patterns using remotely sensed data.International Journal of Wildland Fire 16, 277-284.
Eidenshenk J., Schwind, B., Brewer, K., Zhu, Z., Quayle, B. & Howard, S. (2007). A Project for Monitoring Trends in Burn Severity. Fire Ecology Special Issue. Vol. 3, No. 1.
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(3-4), 328-339.
Escuin, S., Navarro, R., Fernandez, P. (2009). Fire severity assessment by using NBR (Normalized Burn Ratio) and NDVI (Normalized Difference Vegetation Index) derived from LANDSAT TM/ETM Images. International Journal of Remote Sensing, 29(4), 1053-1073.
Fox, D. M., Maselli, F. & Carrega, P. (2008). Using SPOT images and field sampling to map burn severity and vegetation factors affecting post forest fire erosion risk. CATEN, 75(3), 326.-335
French, N.H., Kasischke, E.S., Hall, R.J., Murphy, K.A., Verbyla, D.L., Hoy, E.E. & Allen, J.L. (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.
Hall, R.J., Freeburn, J.T., de Groot, W.J., Pritchard, J.M., Lynham, T.J. & Landry, R. (2008). Remote sensing of burn severity: experience from western Canada boreal fires. International Journal of Wildland Fire 17, 476–489.
Holden, Z.A., Smith, A.M.S., Morgan, P., Rollins, M.G. & Gessler, P.E. (2005). Evaluation of novel thermally enhanced spectral indices for mapping fire perimeters and comparisons with fire atlas data. International Journal of Remote Sensing, 26(21), 4801-4808.
Howard, S.M. & Lacasse, J.M. (2004). An evaluation of gap-filled Landsat SLC-Off imager for wildland fire burn severity mapping, Photogrammetric Engineering and Remote 70, 877–880.
Hoy, E.E., French, N.H., Turetsky, M.R., Trigg, S.N., & Kasischke, E.S. (2008). Evaluating the potential of Landsat TM/ETM+ imagery for assessing fire severity in Alaskan black spruce forests.International Journal of Wildland Fire17, 500–514.
Hudak, A.T., Morgan, P., Bobbitt, M.J., Smith, A.M.S., Lewis, S.A., Lentile, L.B., Robichaud, P. R., Clark, J.T., & McKinley, R.A. (2007). The relationship of multispectral satellite imagery to immediate fire effects. Fire Ecology: 3(1): 64-90.
Keeley, J.E. (2009). Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire 18, 116–126.
Key, C.H. & Benson, N.C. (2005). Landscape assessment: remote sensing of severity, the Normalized Burn Ratio. In: D.C. Lutes et al. (Editors), FIREMON: Fire Effects Monitoring and Inventory System , Ogden, UT: USDA Forest Service, Rocky Mountain Research Station, General Technical Report, RMRS-GTR-164-CD:LA1-LA51.
Key, C.H. 2006. Ecological and sampling constraints on defining landscape fire severity. Fire Ecology: 2(2): 178-203.
Lentile, L.B., Holden, Z.A., Smith, A.M. , Falkowski, M.J., Hudak, A.T., Morgan, P., Lewis, S.A., Gessler, P.E. & Benson, N.C. (2006). Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire 15, 319–345.
Loboda, T., O'Neal, K.J. & Csiszar, I. (2007). Regionally adaptable dNBR-based algorithm for burned area mapping from MODIS data. Remote Sensing of Environment, 109(4), 429-442.
Lopez Garcia, M.J. & Caselles, V. (1991). Mapping burns and natural reforestation using Thematic Mapper data. Geocarto International, 1, 31-37.
Miller, J.D. & Yool, S.R. (2002). Mapping forest post-fire canopy consumption in several overstory types using multi-temporal Landsat TM and ETM data. Remote Sensing of Environment, 82(2-3), 481-496.
Murphy, K.A., Reynolds, J.H. & Koltun, J.M. (2008). Evaluating the ability of the differenced Normalized Burn Ratio (dNBR) to predict ecologically significant burn severity in Alaskan boreal forests. International Journal of Wildland Fire 17, 490–499.
Navarra Cerrillo, R.M., Hayas, A., Garcia-Ferrer, A.C., Clemente, R.H., Duhalde, P., Gonzalez, L. (2008). Characteristics of areas affected by fire in 2005 at Parque Nacional de Torres del Paine (Chile) as assessed from multispectral images. REVISTA CHILENA DE HISTORIA NATURAL, 81 (1), 95-110.
Norton, J., Glenn, N., Germino, M., Weber, K., & Seefeldt, S. (2009). Relative suitability of indices derived from Landsat ETM+ and SPOT 5 for detecting fire severity in sagebrush steppe. International Journal of Applied Earth Observation and Geoinformation, 11(5): 360-367.
Robichaud, P.R., Lewis, S.A., Laes, D.Y.M., Hudak, A.T., Kokaly, R.F. Zamudio, J.A. (2007). Postfire soil burn severity mapping with hyperspectral image unmixing. Remote Sensing of Environment, 108(4), 467-480.
Roy, D.P., Boschetti, L. & Trigg, S.N. (2006). Remote sensing of fire severity: Assessing the performance of the Normalized Burn Ratio. IEEE Geoscience and Remote Sensing Letters, 3(1), 112-116.
Smith, A. M. S., Lentile, L. B., Hudak, A. T. & Morgan, P. (2009). Evaluation of linear spectral unmixing and DNBR for predicting postfire recovery in a North American ponderosa pine forest. International Journal of Remote Sensing, 28(22), 5159-5166.
Soverel, Nicholas O., Perrakis, Daniel D.B., Coops, Nicholas C. (2010). Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada. Remote Sensing of Environment, 114 (9), 1896-1909.
Van Wagtendonk, J.W., Root, R.R. & Key, C.H. (2004). Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity. Remote Sensing of Environment, 92(3), 397-408.
Verbyla, D.L., Kasischke, E.S. & Hoy, E.E. (2008). Seasonal and topographic effects on estimating fire severity from Landsat TM/ETM+ data. International Journal of Wildland Fire 17, 527–534.
Walz, Y., Maier, S.W., Dech, S.W., Conrad, C., Colditz, R.R. (2007). Classification of burn severity using Moderate Resolution Imaging Spectroradiometer (MODIS): a case study in the jarrah-marri forest of south-west Western Australia. Journal of Geophysical Research 112.
White, J.D., Ryan, K.C., Key, C.C. & Running, S.W. (1996). Remote Sensing of Forest Fire Severity and Vegetation Recovery. International Journal of Wildland Fire 6, 125–136.
Wulder, M.A., White, J.C., Alvarez, F., Han, T., Rogan, J., & Hawkes, B. (2009). Characterizing boreal forest wildfire with multi-temporal Landsat and LIDAR data. Remote Sensing of Environment, 113(7), 1540-1555.
Zhu, Z.; Key, C.; Ohlen, D.; Benson, N. (2006). Evaluate Sensitivities of Burn-Severity Mapping Algorithms for Different Ecosystems and Fire Histories in the United States. Final Report to the Joint Fire Science Program, Project JFSP 01-1-4-12, October 12, 2006. 35pp.
References that use NBR/dNBR derived data to solve questions
Hydrological effects:
Cannon, S.H., Gartner, J.E., Rupert, M.G., Michael, J.A., Djokic, D. & Sreedhar, S. (2003). Emergency Assessment of Debris-Flow Hazards from Basins Burned by the Grand Prix and Old Fires of 2003, Southern California. Open-File Report, 03-0475: U.S. Geological Survey.
Lewis, S.A., Wu, J.Q. & Robichaud, P.R. (2006). Assessing burn severity and comparing soil water repellency, Hayman Fire, Colorado. Hydrological Processes, 20(1), 1-16.
Miller, J.D., Nyhan, J.W. & Yool, S.R. (2003). Modeling potential erosion due to the Cerro Grande Fire with a GIS-based implementation of the Revised Universal Soil Loss Equation. International Journal of Wildland Fire, 12(1), 85-100..
Moody, J.A., Martin, D.A., Haire, S.L., & Kinner, D.A.. (2007). Linking runoff response to burn severity after a wildfire. Hydrological Processes, 22, 2063-2074.
Fuel treatment effectiveness:
Finney, M.A., McHugh, C.W. & Grenfell, I.C. (2005). Stand- and landscape-level effects of prescribed burning on two Arizona wildfires. Canadian Journal of Forest Research, 35(7), 1714-1722.
Safford, H.D., Schmidt, D.A., Carlson, C.H. (2009). Effects of fuel treatments on fire severity in an area of wildland-urban interface, Angora Fire, Lake Tahoe Basin, California, Forest Ecology and Management, 258(5), 773-787.
Wimberly, M.C., Cochrane, M.A., Baer, A.D. & Pabst, K. (2009). Assessing fuel treatment effectiveness using satellite imagery and spatial statistics. Ecological Applications, 19(6), 1377-1384.
Landscape level ecosystem processes:
Bigler, C., Kulakowski, D. & Veblen, T.T. (2005). Multiple disturbance interactions and drought influence fire severity in Rocky Mountain subalpine forests. Ecology, 86(11), 3018-3029.
Epting, J. & Verbyla, D. (2005). Landscape-level interactions of prefire vegetation, burn severity, and postfire vegetation over a 16-year period in interior Alaska. Canadian Journal of Forest Research, 35, 1367-1377.
Holden, Z.A., Morgan, P. & Evans, J.S. 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.
Kotliar, N.B., Haire, S.L. & Key, C.H. (2003). Lessons from the fires of 2000: post-fire heterogeneity in Ponderosa pine forests, RMRS-P-29. Conference Proceedings, April 16-18, 2002, Fort Collins, CO: USDA Forest Service, Rocky Mountain Research Station, 277-279 pp.
Lentile, L.B., Smith, A.M., Hudak, A.T., Morgan, P., Bobbitt, M.J., Lewis, S.A. & Robichaud P.R. (2009). Remote sensing for prediction of 1-year post-fire ecosystem condition. International Journal of Wildland Fire 18, 594–608.
Miller, J.D., Knapp, E.E., Key, C.H., Skinner, C.N., Isbell, C.J., Creasy, R.M., & Sherlock, J.W. Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA. Remote Sensing of Environment, 113(3), 645-656.
Miller, J.D. & Thode, A.E. Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR). Remote Sensing of Environment, 109(1), 66-80.
Miller, J.D. & Fites, J. (2006). Sierra Nevada Fire Severity Monitoring: 1984 - 2004. Internal Report, Draft. Nevada City, CA: USDA Forest Service, Pacific Southwest Region, Adaptive Management Services Enterprise Team, 62 pp.
Reinhardt, E.D., Keane, R.E., Brown, J.K. (2001). Modeling fire effects. International Journal of Wildland Fire, 10, 373-380.
Sang-Woo, Lee, Myung-Bo, Lee, Young-Geun, Lee, Myoung-Soo, Won, Jong-Jin, Kim, Sung-kwon, Hong. (2009). Relationship between landscape structure and burn severity at the landscape and class levels in Samchuck, South Korea. Forest Ecology and Management, 258(7), 1594-1604.
Thode, A.E. (2005). Quantifying the Fire Regime Attributes of Severity and Spatial Complexity Using Field and Imagery Data. PhD Dissertation, University of California, Davis, CA.
Wimberly, M.C. & Reilly, M.J. (2007). Assessment of fire severity and species diversity in the southern Appalachians using Landsat TM and ETM+ imagery. Remote Sensing of Environment, 108(2), 189-197.
Posters:
Brewer, C.K., Schwind, B., Queen, L., Quayle, B. & Eidenshink, J. (2007). Alternative Landscape Pattern Analyses using MTBS Historical Burn Severity Data. Proceedings of Climate Change Impacts on Boreal Forest Disturbance Regimes, Fairbanks, AK, May 30 – June 2, 2007.
Howard, S. (2005). Monitoring Trends in Burn Severity. USGS Wildland Fire Science Workshop. Tucson, AZ, December 6-9, 2005.
Key, C.H. & Benson, N.C. (1999). Measuring and Remote Sensing of Burn Severity: the CBI and NBR. Proceedings of Joint Fire Science Conference and Workshop, Volume 2, Boise, ID, June 15-17, 1999. University of Idaho and International Association of Wildland Fire. 284 pages.
Schwind, B., Eidenschenk, J. & Quayle, B. (2008). Historical Fire Severity Data in the Southwestern United States: Results from the Monitoring Trends in Burn Severity Project. Association for Fire Ecology Regional Conference 2008 Fire in the Southwest: Integrating Fire into Management of Changing Ecosystems, Tucson, AZ, January 28-31, 2008. The Association of Fire Ecology.