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


  • S. Martínez Universidad de Alcalá
  • E. Chuvieco Universidad de Alcalá
  • I. Aguado Universidad de Alcalá
  • J. Salas Universidad de Alcalá




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


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.


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Author Biographies

S. Martínez, Universidad de Alcalá

Depto. de Geología, Geografía y Medio Ambiente

E. Chuvieco, Universidad de Alcalá

Depto. de Geología, Geografía y Medio Ambiente

I. Aguado, Universidad de Alcalá

Depto. de Geología, Geografía y Medio Ambiente

J. Salas, Universidad de Alcalá

Depto. de Geología, Geografía y Medio Ambiente


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