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Development of a framework for fire risk assessment using remote sensing and geographic information system technologies

AuthorsChuvieco, Emilio; Aguado, Inmaculada; Yebra, Marta; Nieto, Héctor; Salas, Javier; Martín, M. Pilar ; Vilar del Hoyo, Lara ; Martínez Vega, Javier ; Martín, Susana ; Ibarra, Paloma; Riva, Juan de la; Baeza, Jaime; Rodríguez, Francisco; Molina, Juan R.; Herrera, Miguel A.; Zamora, Ricardo
KeywordsFire risk
Fire danger
Geographic information systems
Remote sensing
Logistic regression
Human factors
Fuel moisture content
Issue Date2010
CitationEcological Modelling 221(1): 46-58 (2010)
AbstractForest fires play a critical role in landscape transformation, vegetation succession, soil degradation and air quality. Improvements in fire risk estimation are vital to reduce the negative impacts of fire, either by lessen burn severity or intensity through fuel management, or by aiding the natural vegetation recovery using post-fire treatments. This paper presents the methods to generate the input variables and the risk integration developed within the Firemap project (funded under the Spanish Ministry of Science and Technology) to map wildland fire risk for several regions of Spain. After defining the conceptual scheme for fire risk assessment, the paper describes the methods used to generate the risk parameters, and presents proposals for their integration into synthetic risk indices. The generation of the input variables was based on an extensive use of geographic information system and remote sensing technologies, since the project was intended to provide a spatial and temporal assessment of risk conditions. All variables were mapped at 1 km2 spatial resolution, and were integrated into a web-mapping service system. This service was active in the summer of 2007 for semi-operational testing of end-users. The paper also presents the first validation results of the danger index, by comparing temporal trends of different danger components and fire occurrence in the different study regions.
Publisher version (URL)http://dx.doi.org/10.1016/j.ecolmodel.2008.11.017
Appears in Collections:(CCHS-IEGD) Artículos
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