Burn severity and regeneration in large forest fires: an analysis from Landsat time series

S. Martínez, E. Chuvieco, I. Aguado, J. Salas


The main objective of this study is to take a close look at post-fire recovery patterns in forestry areas under different burn severity conditions. We also investigate the time that forestry ecosystems take to recover their pre-fire condition. In this context, this study analyses both the level of severity in Uncastillo forest wildfire (7.664ha), one of the greatest occurred in Spain in 1994, and the pattern of natural recovery in the following decades (until 2014) using annual Landsat time series (sensors TM&ETM+). Burn severity has been estimated by means of PROSPECT and GeoSAIL radiative transfer models following methodologies described in De Santis and Chuvieco (2009). On the other hand, recovery processes have been assessed from spectral profiles using the LandTrendr model (Landsat-based Detection of Trends in Disturbance and Recovery) (Kennedy et al., 2010). Results contribute to a further understanding of the post-fire evolution in forestry areas and to develop effective strategies for sustainable forest management.


Wildland fires; GeoCBI; recovery; burn severity; LandTrendr; LandsaT

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Bastarrika, A., Alvarado, M., Artano, K., Martínez, M. P., Mesanza, A., Torre, L., Chuvieco, E. 2014. BAMS: A Tool for Supervised Burned Area Mapping Using Landsat Data. Remote Sensing, 6, 12360-12380. https://doi.org/10.3390/rs61212360

Chuvieco, E. 2016. Fundamentals of Satellite Remote Sensing: An Environmental Approach. Boca Raton (FL): CRC Press.

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. https://doi. org/10.1016/j.rse.2008.10.011

Díaz-Delgado, R., Lloret, F., Pons, X. 2003. Influence of fire severity on plant regeneration by means of remote sensing imagery. International Journal of Remote Sensing, 24(8), 1751-1763. https://doi. org/10.1080/01431160210144732

Doerr, S. H., Shakesby, R. A., Blake, W. H., Chafer, C. J., Humphreys, G. S., Wallbrink, P. J. 2006. Effects of differing wildfire severities on soil wettability and implications for hydrological response. Journal of Hydrology, 319, 295-311. https://doi.org/10.1016/j. jhydrol.2005.06.038

Frolking, S., Palace, M. W., Clark, D. B., Chambers, J. Q., Shugart, H. H., Hurtt, G. C. 2009. Forest disturbance and recovery: A general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure. Journal of Geophysical Research-Biogeosciences, 114. https://doi.org/10.1029/2008JG000911

Grogan, K., Pflugmacher, D., Hostert, P., Kennedy, R. E., Fensholt, R. 2015. Cross-border forest disturbance and the role of natural rubber in mainland Southeast Asia using annual Landsat time series. Remote Sensing of Environment, 169, 438-453. https://doi. org/10.1016/j.rse.2015.03.001

Ireland, G., Petropoulos, G. P. 2015. Exploring the relationships between post-fire vegetation regeneration dynamics, topography and burn severity: A case study from the Montane Cordillera Ecozones of Western Canada. Applied Geography, 56, 232-248. https://doi.org/10.1016/j. apgeog.2014.11.016

Jin, Y., Randerson, J. T., Goetz, S. J., Beck, P. S., Loranty, M. M., Goulden, M. L. 2012. The influence of burn severity on postfire vegetation recovery and albedo change during early succession in North American boreal forests. Journal of Geophysical Research: Biogeosciences, 117. https://doi. org/10.1029/2011JG001886

Kennedy, R. E., Andréfouët, S., Cohen, W. B., Gómez, C., Griffiths, P., Hais, M., Zhu, Z. 2014. Bringing an ecological view of change to Landsat-based remote sensing. Frontiers in Ecology and the Environment, 12(6), 339-346. https://doi.org/10.1890/130066

Kennedy, R. E., Townsend, P. A., Gross, J. E., Cohen, W. B., Bolstad, P., Wang, Y. Q., Adams, P. 2009. Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects. Remote Sensing of Environment, 113(7), 1382-1396. https:// doi.org/10.1016/j.rse.2008.07.018

Kennedy, R. E., Yang, Z., Cohen, W. B. 2010. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms. Remote Sensing of Environment, 114, 2897-2910. https://doi. org/10.1016/j.rse.2010.07.008

Key, C. H., Benson, N. 2006. Landscape Assessment (LA). Sampling and Analysis Methods. In D.C. Lutes, R.E. Keane, J.F. Caratti, & et al. (Eds.), FIREMON: Fire effects monitoring and inventory system. Integration of Standardized Field Data Collection Techniques and Sampling Design With Remote Sensing to Assess Fire Effects (pp. LA1- LA51). Fort Collins, CO, US: Dept. of Agriculture, Forest Service, Rocky Mountain Research Station.

Lentile, L. B., Holden, Z. A., Smith, A. M. S., Falkowski, M. J., Hudak, A. T., Morgan, P., Benson, N. C. 2006. Remote sensing techniques to assess active fire characteristics and post-fire effects. International Journal of Wildland Fire, 15(3), 319-345. https:// doi.org/10.1071/WF05097

Lentile, L. B., Morgan, P., Hudak, A. T., Bobbitt, M. J., Lewis, S. A., Smith, A. M. S., Robichaud, P. R. 2007. Post-fire burn severity and vegetation response following eight large wildfires across the western United States. Fire Ecology, 3(1), 91-108. https://doi.org/10.4996/fireecology.0301091

Masek, J. G., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F. G., Huemmrich, K. F., Lim, T. K. 2006. A Landsat Surface Reflectance Dataset for North America, 1990–2000. IEEE Geoscience and Remote Sensing Letters, 3(1), 68-72. https://doi.org/10.1109/ LGRS.2005.857030

Masek, J. G., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F. G., Huemmrich, K. F., Lim, T. K. 2012. LEDAPS Landsat Calibration, Reflectance, Atmospheric Correction Preprocessing Code. ORNL DAAC. Retrieved from Oak Ridge, Tennessee, USA:

Meng, J., Dennison, P. E., Huang, C. H., Moritz, M. A., D’Antonio, C. M. 2015. Effects of fire severity and post-fire climate on short-term vegetation recovery of mixed-conifer and red fir forests in the Sierra Nevada Mountains of California. Remote Sensing of Environment, 171, 311-325. https://doi. org/10.1016/j.rse.2015.10.024

Moody, J. A., Shakesby, R. A., Robichaud, P. R., Cannon, S. H., Martin, D. A. 2013. Current research issues related to post-wildfire runoff and erosion processes. Earth-Science Reviews, 122, 10-37. https://doi.org/10.1016/j.earscirev.2013.03.004

Oliva, P., Martin, P., Chuvieco, E. 2011. Burned area mapping with MERIS post-fire image. International Journal of Remote Sensing, 32(15), 4175-4201. https://doi.org/10.1080/01431161.2010.489062

Pausas, J. 2012. Incendios Forestales. Una visión desde la Ecología. Madrid: CSIC. Catarata. https://doi. org/10.1016/j.rse.2013.05.033

Riaño, D., Chuvieco, E., Ustin, S., Zomer, R., Dennison, P., Roberts, D., Salas, J. 2002. Assessment of vegetation regeneration after fire through multitemporal analysis of AVIRIS images in the Santa Monica Mountains. Remote Sensing of Environment, 79(1), 60-71. https://doi.org/10.1016/ S0034-4257(01)00239-5

Veraverbeke, S., Hook, S., y Hulley, G. 2012. An alternative spectral index for rapid fire severity assessments. Remote Sensing of Environment, 123, 72-80. https://doi.org/10.1016/j.rse.2012.02.025

Veraverbeke, S., Hook, S. J. 2013. Evaluating spectral indices and spectral mixture analysis for assessing fire severity, combustion completeness and carbon emissions. Journal of the International Association of Wildland Fire, 22(5), 707-720. https://doi. org/10.1071/WF12168

Vermote, E. F., Saleous, N. E., Justice, C. O., Kaufman, Y. J., Privette, J. L., Remer, L., Tanré, D. 1997. Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation. Journal of Geophysical Research, 102(14), 17131-117141. https://doi.org/10.1029/97JD00201

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. https://doi.org/10.1071/ WF9960125

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Universitat Politècnica de València

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