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Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Assessment of the influence of biophysical properties related to fuel conditions on fire severity using remote sensing techniques: a case study on a large fire in NW Spain

Paula García-Llamas https://orcid.org/0000-0003-1351-7853 A D , Susana Suárez-Seoane A , Angela Taboada A , Victor Fernández-García https://orcid.org/0000-0003-3217-3814 A , José M. Fernández-Guisuraga A , Alfonso Fernández-Manso B , Carmen Quintano C , Elena Marcos A and Leonor Calvo A
+ Author Affiliations
- Author Affiliations

A Biodiversity and Environmental Management Department, Faculty of Biological and Environmental Sciences, University of León, 24071 León, Spain.

B Agrarian Science and Engineering Department, University of León, Avenida Astorga s/n, 24400 Ponferrada, Spain.

C Electronic Technology Department, Sustainable Forest Management Research Institute, University of Valladolid, Spanish National Institute for Agriculture and Food Research and Technology (INIA), C/ Paseo del Cauce, 59, 47011 Valladolid, Spain.

D Corresponding author. Email: pgarcl@unileon.es

International Journal of Wildland Fire 28(7) 512-520 https://doi.org/10.1071/WF18156
Submitted: 19 September 2018  Accepted: 14 May 2019   Published: 20 June 2019

Abstract

This study analyses the suitability of remote sensing data from different sources (Landsat 7 ETM+, MODIS and Meteosat) in evaluating the effect of fuel conditions on fire severity, using a megafire (11 891 ha) that occurred in a Mediterranean pine forest ecosystem (NW Spain) between 19 and 22 August 2012. Fire severity was measured via the delta Normalized Burn Ratio index. Fuel conditions were evaluated through biophysical variables of: (i) the Visible Atmospherically Resistant Index and mean actual evapotranspiration, as proxies of potential live fuel amount; and (ii) Land Surface Temperature and water deficit, as proxies of fuel moisture content. Relationships between fuel conditions and fire severity were evaluated using Random Forest models. Biophysical variables explained 40% of the variance. The Visible Atmospherically Resistant Index was the most important predictor, being positively associated with fire severity. Evapotranspiration also positively influenced severity, although its importance was conditioned by the data source. Live fuel amount, rather than fuel moisture content, primarily affected fire severity. Nevertheless, an increase in water deficit and land surface temperature was generally associated with greater fire severity. This study highlights that fuel conditions largely determine fire severity, providing useful information for defining pre-fire actions aimed at reducing fire effects.

Additional keywords: evapotranspiration, fire effects, Landsat, Meteosat, MODIS, VARI index.


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