The UJI spread the research done to do forest fires risk maps

Pablo Juan , Carlos Diaz Avlos and I (Pau Aragó) has been working in a research on Castellón (Spain) forest fires to do risk maps. The Jaume I University has consider this work interesting. As a result the Communication Department has done this report.

The UJI designs a model of risk maps of forest fires that incorporates the human factor

Researchers have used a statistical tool to prevent forest fires

Researchers from the Department of Mathematics at the Universitat Jaume I (UJI) have

designed a statistical model of forest fire prevention that includes the risk posed by human factors, such as the proximity of the woodlands to roads. The findings of this study have been published in the European Journal of Forest Research.

UJI’s research has used the actual data, provided by the Valencian Regional Government (Generalitat Valenciana), of the 663 forest fires recorded in the province of Castelló between 2001 and 2006. “Our goal in this first phase of the study was to incorporate both physical and socioeconomic variables –influence of the environment, population characteristics, urban conflicts, etc.– with the aim of improving the existing fire hazard maps based on simulations”, explained the researchers from the Department of Mathematics Pau Aragó and Pablo Juan.

The two most important variables provided by the fire model created by the UJI are the type of vegetation and the proximity to roads, which would be added to other risks such as temperature, accumulated rainfall or wind speed. Juan and Aragó claim that their team’s work “demonstrates the strong human component of the distribution of fires in Castelló during the study period, a trend that, in our view, could be extended to the rest of the Valencian territory”.

Pablo Juan, lecturer of Statistics and Operations Research, states that they compared the incidence of two major types of fires: those of natural origin and those caused by human activity. “It was the continuation of previous works which had analysed the fires recorded in Castelló, but without comparing these two possible causes”, he assures. In fact, previous studies “have helped us to know the fire behaviour patterns and to show whether they are grouped, homogeneous or with inhibition, all of which is important to work with point process statistics, adds Juan.

RISK LINKED TO POPULATION DENSITY

The scientists at the Universitat Jaume I recommend that the human factor is incorporated as a risk variable of forest fires. The danger of fire, in the words of Pau Aragó, “clearly increases when there is a high population density. Thus, the coastal area, where there is less forest area, presents a higher risk of fire”. In parallel, “in inland areas, with more forest resources and more depopulated, as in the case of the region of Els Ports, stands out the risk of fire due to natural causes, which highlights the impact of lightning during episodes of dry storms”, explains the researcher.

The incidence of forest fires has increased in the European Mediterranean region in recent decades. This trend is related in part to the increase in average temperatures and low levels of relative humidity. In addition, according to the UJI researchers, “in turn, socioeconomic variables have also had an influence, and they have also led to the abandonment of rural areas and, consequently, to an increase in the accumulation of forest fuel in the mountains”.

Pau Aragon’s and Pablo Juan’s work has combined forest knowledge and geographic information systems (GIS) with the application of spatial statistics to implement these tools to the studies on forest fire prevention. This research is part of a larger project developed by the group led by the professor of Statistics and Operations Research from the Department of Mathematics, Jorge Mateu. This line of research lies within the context of mathematical and statistical modelling in both environmental issues and in the field of criminology. The researchers used spatiotemporal stochastic processes and techniques, characterized by randomness, for modelling and prediction purposes.

Videonews on CiènciaUJI TV (Original video in Spanish with English subtitles).

Aragó, P., P. Juan, C. Díaz-Avalos, P. Salvador. «Spatial Point Process Modelling Applied to the Assessment of Risk Factors Associated with Forest Wildfires Incidence in Castellón, Spain». European Journal of Forest Research, 26 February 2016, doi: 10.1007/s10342-016-0945-z.

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