Retrospective analysis of two northern California wild-land fires via Landsat five satellite imagery and Normalized Difference Vegetation Index (NDVI)


Wild-land fires are a dynamic and destructive force in natural ecosystems. In recent decades, fire disturbances have increased concerns and awareness over significant economic loss and landscape change. The focus of this research was to study two northern California wild-land fires: Butte Humboldt Complex and Butte Lightning Complex of 2008 and assessment of vegetation recovery after the fires via ground based measurements and utilization of Landsat 5 imagery and analysis software to assess landscape change. Multi-temporal and burn severity dynamics and assessment through satellite imagery were used to visually ascertain levels of landscape change, under two temporal scales. Visual interpretation indicated noticeable levels of landscape change and relevant insight into the magnitude and impact of both wild-land fires. Normalized Burn Ratio (NBR) and delta NBR (DNBR) data allowed for quantitative analysis of burn severity levels. DNBR results indicate low severity and low re-growth for Butte Humboldt Complex “burned center” subplots. In contrast, DNBR values for Butte Lightning Complex “burned center” subplots indicated low-moderate burn severity levels.

Share and Cite:

Sall, B. , Jenkins, M. and Pushnik, J. (2013) Retrospective analysis of two northern California wild-land fires via Landsat five satellite imagery and Normalized Difference Vegetation Index (NDVI). Open Journal of Ecology, 3, 311-323. doi: 10.4236/oje.2013.34036.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Calfire (2010)
[2] Conedera, M., Tinner, W., Neff, C., Meurer, M., Dickens, A. and Krebs, P. (2008) Reconstructing past fire regimes: Methods, applications, and relevance to fire management and conservation. Quaternary Science Reviews, 28, 555-576. doi:10.1016/j.quascirev.2008.11.005
[3] Taylor, A. and Beaty, R. (2005) Climate influences of fire regimes in northern Sierra Nevada Mountains, Lake Tahoe Basin, Nevada, USA. Journal of Biogeography, 32, 425-438. doi:10.1111/j.1365-2699.2004.01208.x
[4] Fried, J., Torn, M. and Mills, E. (2004) The impact of climate change on wildfire severity: A regional forecast for Northern California. Climatic Change, 64, 161-191. doi:10.1023/B:CLIM.0000024667.89579.ed
[5] Flannigan, M.D., Stocks, B.J. and Wotton, B.M. (2000) Climate change and forest fires. Science of the Total Environment, 262, 221-229. doi:10.1016/S0048-9697(00)00524-6
[6] Dale, V.H., Joyce, L.A., McNulty, S., Neilson, R.P., Ayres, M.P., Flannigan, M.D., Hanson, P.J., Irland, L.C., Lugo, A.E., Peterson, C.J., Simberloff, D., Swanson, F.J., Stocks, B.J. and Wotton, B.M. (2001) Climate change and forest disturbances. BioScience, 51, 723. doi:10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2
[7] Whitlock, C., Shafer, S.L. and Marlon, J. (2003) The role of climate and vegetation change in shaping past and future fire regimes in the northwestern US and the implications for ecosystem management. Forest Ecology and Management, 178, 5-21. doi:10.1016/S0378-1127(03)00051-3
[8] Zomer, R.J., Trabucco, A. and Ustin, S.L. (2009) Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing. Journal of Environmental Management, 90, 2170-2177. doi:10.1016/j.jenvman.2007.06.028
[9] Sims, D.A. and Gamon, J.A. (2003) Estimation of vegetation water content and photosynthetic tissue area from spectral reflectance: A comparison of indices based on liquid water and chlorophyll absorption features. Remote Sensing of Environment, 84, 526-537. doi:10.1016/S0034-4257(02)00151-7
[10] Chandler, C., Cheney, P., Thomas, P., Trabaud, L. and William, D. (1983) Fire in forestry. Forest Fire Behavior and Effects, Vol. I. John Wiley & Sons Ltd., New York.
[11] Penuelas, J., Filella, I., Biel, C., Serrano, L. and Savé, R. (1993) The reflectance at the 950 970 nm region as an indicator of plant water status. International Journal of Remote Sensing, 14, 1887-1905. doi:10.1080/01431169308954010
[12] Penuelas, J., Pinol, J., Ogaya, R. and Filella, I. (1997) Estimation of plant water concentration by the reflective water index WI (R900/R970). International Journal of Remote Sensing, 18, 2869-2875. doi:10.1080/014311697217396
[13] Filella, I., Penuelas, J., Llorens, L. and Estiarte, M. (2004) Reflectance assessment of seasonal and annual changes in biomass and CO2 uptake of Mediterranean shrubland submitted to experimental warming and drought. Remote Sensing of Environment, 90, 308-318. doi:10.1016/j.rse.2004.01.010
[14] Veraverbeke, S., Verstraeten, W.W., Lhermitte, S. and Goossens, R. (2010) Evaluating Landsat Thematic Mapper spectral indices for estimating burn severity of the 2007 Peloponnese wildfires in Greece. International Journal of Wildland Fire, 19, 558-569. doi:10.1071/WF09069
[15] Pettorelli, N., Olav Vik, J., Mysterud, A., Gaillard, J.M., Tucker, C.J. and Stenseth, N.C. (2005) Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution, 20, 503-510. doi:10.1016/j.tree.2005.05.011
[16] Lichtenhaler, H.K., Wenzel, O., Buschmann, C. and Gitelson, A. (1998) Plant stress detection by reflectance and fluorescence. Annals of the New York Academy of Sciences, 851, 271-285. doi:10.1111/j.1749-6632.1998.tb09002.x
[17] Guerschman, J.P., Paruelo, J.M. and Burke, I.C. (2003) Land use impacts on the Normalized Vegetation Index in temperate Argentina. Ecological Applications, 13, 616-628. doi:10.1890/1051-0761(2003)013[0616:LUIOTN]2.0.CO;2
[18] Tucker, C.J. (1979) Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8, 127-150. doi:10.1016/0034-4257(79)90013-0
[19] Salazar. L., Kogan, F. and Roytman, L. (2007) Use of remote sensing data for estimation of winter wheat yield in the United States. International Journal of Remote Sensing, 28, 3795-3811. doi:10.1080/01431160601050395
[20] Rosso, P.H., Pushnik, J.C., Lay, M. and Ustin, S.L. (2005) Reflectance properties and physiological responses of Salicornia virginica to heavy metal and petroleum contamination. Environmental Pollution, 137, 241-252. doi:10.1016/j.envpol.2005.02.025
[21] Ustin, S.L. and Gamon, J.A. (2010) Remote sensing of plant functional types. New Phytologist, 186, 795-816. doi:10.1111/j.1469-8137.2010.03284.x
[22] Horning, N., Robinson, J.A., Sterling, E.J., Turner, W. and Spector, S. (2010) Remote sensing for ecology and conservation: A handbook of techniques. Oxford University Press, New York, 4-371.
[23] Inoue, Y. (2003) Synergy of remote sensing and modeling for estimating ecophysiological processes in plant production. Plant Production Science, 6, 3-16.
[24] Black, S.C. and Guo, X. (2008) Estimation of grassland CO2 exchange rates using hyperspectral remote sensing techniques. International Journal of Remote Sensing, 29, 145-155. doi:10.1080/01431160701253220
[25] US Geological Survey (2011)
[26] ENVI 4.8 (2010) Exelis visual information solutions. Boulder, CO.
[27] Epting, J., Verbyla, D. and 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. doi:10.1016/j.rse.2005.03.002
[28] Soverel, N.O., Perrakis, D.D.B. and Coops, N.C. (2010) Estimating burn severity for Landsat dNBR and RdNBR indices across western Canada. Remote Sensing of Environment, 114, 1896-1909. doi:10.1016/j.rse.2010.03.013
[29] Smith, A.M.S., Lentile, L.B., Hudak, A.T. and Morgan, P. (2007) Evaluation of linear spectral unmixing and NBR for predicting post-fire recovery in a North American ponderosa pine forest. International Journal of Remote Sensing, 28, 5159-5166. doi:10.1080/01431160701395161
[30] Key, C.H. and Benson, N.C. (2006) Landscape assessment: Sampling and analysis methods: Firemon: Fire effects monitoring and inventory system. General Technical Report. USDA Forest Service, Rocky Mountain Research Station, Fort Collins CO., RMRS-GTR-164-CD.
[31] Van Wagtendonk, J.W., Root, R.R. and Key, C.C. (2004) Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity. Remote Sensing of Environment, 92, 397-408.
[32] Miller, J.D. and Thode, A.E. (2007) Quantifying burn severity in a heterogeneous landscape with a relative version of the data Normalized Burn Ratio (dNBR). Remote Sensing of Environment, 109, 66-80. doi:10.1016/j.rse.2006.12.006
[33] Skinner, C. and Chang, C. (1996) Fire regimes, past and present. Sierra Nevada Ecosystem Project: final report to Congress.
[34] Barbour, M.G. and Major, J. (1977) Terrestrial vegetation of California. University of California Davis, Davis, 18-906.
[35] Garmin (2008) Garmin International Inc. KS 66062, Olathe.
[36] Unispec, S.C. (2008) PP Systems International Inc., Amesbury.
[37] Letts, M.G., Phelan, C.A., Johnson, D.R.E. and Rood, S.B. (2008) Seasonal photosynthetic gas exchange and leaf reflectance characteristics of male and female cottonwoods in a riparian woodland. Tree Physiology, 28, 1037-1048. doi:10.1093/treephys/28.7.1037
[38] Jenkins, M., Krofcheck, J.D., Pushnik, J., Teasdale, R. and Houpis, J. (2012) Exploring the edge of a natural disaster. Open Journal of Ecology, 2, 222-232.
[39] Furuuchi, H., Jenkins, M., Houpis, J., Senock, R. and Pushnik, J. (2013) Estimating plant crown transpiration and water use efficiency by vegetative reflectance indices associated with chlorophyll fluorescence. Open Journal of Ecology, 3, 122-132.
[40] Vicente-Serrano, S.M., Perez-Cabello, F. and Lasanta, T. (2011) Pinus halepensis regeneration after a wildfire in a semiarid environment: Assessment using multitemporal Landsat images. International Journal of Wildland Fire, 20, 195-208. doi:10.1071/WF08203
[41] Hernandez-Clemente R., Cerrillo R.M., HernandezBermejo, J.E., Royo, S. and Kasimis, N.A. (2009) Analysis of postfire vegetation dynamics of Mediterranean shrub species based on terrestrial and NDVI data. Environmental Management, 43, 876-887. doi:10.1007/s00267-008-9260-x
[42] Van Leeuwen, W.J.D., Casady G.M., Neary, D.G., Bautista, S., Alloza, J.A., Carmel, Y., Wittenberg, L., Malkinson, D. and Orr, B.J. (2010) Monitoring post-wildfire vegetation response with remotely sensed time series data in Spain, USA and Israel. International Journal of Wildland Fire, 19, 75-93. doi:10.1071/WF08078
[43] Ustin, S.L. and Xiao, Q.F. (2001) Mapping successional boreal forests in interior central Alaska. International Journal of Remote Sensing, 22, 1779-1797.
[44] Chen, X., Vierling, L. and Deerling, D. (2005) A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sensing of the Environment, 98, 63-79. doi:10.1016/j.rse.2005.05.021
[45] Paruelo, J.M. and Lauenroth, W.K. (1995) Regional patterns of normalized difference vegetation index in North American shrublands and grasslands. Ecology, 76, 1888-1898. doi:10.2307/1940721
[46] Gomez-Mendoza, L., Galicia, L., Cuevas-Fernandez, M.L., Magana, V., Gomez, G. and Palacio-Prieto, J.L. (2008) Assessing onset and length of greening period in six vegetation types in Oaxaca, Mexico, using NDVIprecipitation relationships. International Journal Biometeorology, 52, 511-520. doi:10.1007/s00484-008-0147-6
[47] National Oceanic and Atmospheric Administration (2010)
[48] Zhong, L., Ma, Y., SuhybSalama, M. and Su, Z. (2010) Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau. Climatic Change, 103, 519-535. doi:10.1007/s10584-009-9787-8
[49] Lloret, F., Lobo, A., Estevan, H., Maisongrande, P., Vayreda, J. and Terradas, J. (2007) Woody plant richness and NDVI response to drought events in Catalonian (northeastern Spain) forests. Ecology, 88, 2270-2279. doi:10.1890/06-1195.1
[50] Kobziar, L.N. and McBride, J.R. (2006) Wildfire burn patterns and riparian vegetation response along two northern Sierra Nevada streams. Forest Ecology and Management, 222, 254-265. doi:10.1016/j.foreco.2005.10.024
[51] Kavgaci, A., Carni, A., Basaran, S., Basaran, M.A., Kosir, P., Marinsek, A. and Silc, U. (2010) Long-term post-fire succession of Pinus brutia forest in the east Mediterranean. International Journal of Wildland Fire, 19, 599-605. doi:10.1071/WF08044
[52] Tarrega, R. and Calabuig, E.L. (1987) Effects of fire on structure dynamics and regeneration of Quercus pyrenaica ecosystems. Ecologia Mediterranea, 13, 79-86.
[53] Keeley, J.E., Brennan, T. and Pfaff, A.H. (2008) Fire severity and ecosystem responses following crown fires in California shrublands. Ecological Applications, 18, 1530-1546. doi:10.1890/07-0836.1
[54] Epting, J., Verbyla, D. and 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. doi:10.1016/j.rse.2005.03.002
[55] Perry, D.A., Hessburg, P.F., Skinner, C.N., Spies, T.A., Stephens, S.L., Taylor, A.H., Franklin, J.F., McComb, B. and Riegel, G. (2011) The ecology of mixed severity fire regimes in Washington, Oregon, and Northern California. Forest Ecology and Management, 262, 703-717. doi:10.1016/j.foreco.2011.05.004

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.