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Calibration of the Fire Weather Index over Mediterranean Europe based on fire activity retrieved from MSG satellite imagery

Carlos C. DaCamara A E , Teresa J. Calado A , Sofia L. Ermida A , Isabel F. Trigo A C , Malik Amraoui A B and Kamil F. Turkman D

A Instituto Dom Luiz (IDL), Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Edifício C8, Piso 3, PT-1749-016 Lisboa, Portugal.
B Universidade de Trás-os-Montes e Alto Douro (UTAD), Escola de Ciências e Tecnologia, Quinta de Prados, PT-5001-801 Vila Real, Portugal.
C Instituto Português do Mar e da Atmosfera (IPMA), Rua C do Aeroporto, Piso 3, PT-1749-077 Lisboa, Portugal.
D Departamento de Estatística e Investigação Operacional (DEIO), Centro de Estatística e Aplicações da Universidade de Lisboa (CEAUL), Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Edifício C6, Piso 4, PT-1749-016 Lisboa, Portugal.
E Corresponding author. Email: cdcamara@fc.ul.pt

International Journal of Wildland Fire - http://dx.doi.org/10.1071/WF13157
Submitted: 10 June 2012  Accepted: 23 April 2014   Published online: 8 August 2014


 
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Abstract

Here we present a procedure that allows the operational generation of daily maps of fire danger over Mediterranean Europe. These are based on integrated use of vegetation cover maps, weather data and fire activity as detected by remote sensing from space. The study covers the period of July–August 2007 to 2009. It is demonstrated that statistical models based on two-parameter generalised Pareto (GP) distributions adequately fit the observed samples of fire duration and that these models are significantly improved when the Fire Weather Index (FWI), which rates fire danger, is integrated as a covariate of scale parameters of GP distributions. Probabilities of fire duration exceeding specified thresholds are then used to calibrate FWI leading to the definition of five classes of fire danger. Fire duration is estimated on the basis of 15-min data provided by Meteosat Second Generation (MSG) satellites and corresponds to the total number of hours in which fire activity is detected in a single MSG pixel during one day. Considering all observed fire events with duration above 1 h, the relative number of events steeply increases with classes of increasing fire danger and no fire activity was recorded in the class of low danger. Defined classes of fire danger provide useful information for wildfire management and are based on the Fire Risk Mapping product that is being disseminated on a daily basis by the EUMETSAT Satellite Application Facility on Land Surface Analysis.

Additional keywords: fire danger, fire management, generalised Pareto distribution, remote sensing, weather.


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