Estudio de la severidad post-incendio en la Comunidad Valenciana comparando los índices dNBR, RdNBR y RBR a partir de imágenes Landsat 8

M. A. Botella-Martínez; A. Fernández-Manso

doi:10.4995/raet.2017.7095

Authors

M. A. Botella-Martínez Vaersa (Generalitat Valenciana)
A. Fernández-Manso Universidad de León

DOI:

https://doi.org/10.4995/raet.2017.7095

Keywords:

post-fire severity, initial assessment, Mediterranean area, Landsat 8, dNBR, RdNBR, RBR, classification thresholds

Abstract

In Mediterranean territories, with their characteristic climate that implies long periods of drought and rains often concentrated in torrential episodes, forest managers are faced with a series of decisions that can be urgent after a wildfire, some of them strongly correlated with the degree of damage caused by fire. In this sense, the object of this study was to provide a fast and reliable tool for the initial assessment of post-fire severity in these kinds of territories, by means of remote sensing techniques. Using Landsat 8 imagery, we have calculated three fire severity indices (dNBR, RdNBR, and RBR) for nine fires occurred in the Valencia region, a typical Mediterranean area. For each index, post-fire severity classification thresholds have been obtained taking into account the following categories: unburned, low, moderate, and high. These thresholds have been validated using, as ground-reference, aerial photographs taken from a helicopter. Afterwards, the degree to which post-fire severity was influenced by factors associated with pre-fire vegetation was evaluated, using a variance analysis. This analysis served to compare the three indices in terms of their robustness against the influence of these factors. With the obtained data, and with the study of classification accuracies employing the Kappa statistic, we were able to propose the most suitable index for calculating post-fire severity in the Valencia region, along with its operating thresholds. The findings suggest that the results could be extrapolated to other areas of similar characteristics.

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