Mapping regional patterns of large forest fires in Wildland–Urban Interface areas in Europe

Abstract

Over recent decades, Land Use and Cover Change (LUCC) trends in many regions of Europe have reconfigured the landscape structures around many urban areas. In these areas, the proximity to landscape elements with high forest fuels has increased the fire risk to people and property. These Wildland-Urban Interface areas (WUI) can be defined as landscapes where anthropogenic urban land use and forest fuel mass come into contact. Mapping their extent is needed to prioritize fire risk control and inform local forest fire risk management strategies. This study proposes a method to map the extent and spatial patterns of the European WUI areas at continental scale. Using the European map of WUI areas, the hypothesis is tested that the distance from the nearest WUI area is related to the forest fire probability. Statistical relationships between the distance from the nearest WUI area, and large forest fire incidents from satellite remote sensing were subsequently modelled by logistic regression analysis. The first European scale map of the WUI extent and locations is presented. Country-specific positive and negative relationships of large fires and the proximity to the nearest WUI area are found. A regional-scale analysis shows a strong influence of the WUI zones on large fires in parts of the Mediterranean regions. Results indicate that the probability of large burned surfaces increases with diminishing WUI distance in touristic regions like Sardinia, Provence-Alpes-Côte d'Azur, or in regions with a strong peri-urban component as Catalunya, Comunidad de Madrid, Comunidad Valenciana. For the above regions, probability curves of large burned surfaces show statistical relationships (ROC value > 0.5) inside a 5000 m buffer of the nearest WUI. Wise land management can provide a valuable ecosystem service of fire risk reduction that is currently not explicitly included in ecosystem service valuations. The results re-emphasise the importance of including this ecosystem service in landscape valuations to account for the significant landscape function of reducing the risk of catastrophic large fires.

Mapping Canadian wildland fire interface areas

“…Disregarding differences in methodology, it appears WUI in Canada does cover a smaller area and proportion of the country compared with WUI in the United States. Modugno et al (2016) studied WUI in European countries. Total areas of WUI were not provided, but percentages of each country covered by WUI ranged from 0.1 to 17.4%, with an average of 3.5% (standard deviation 3.6%).…”

“…Total areas of WUI were not provided, but percentages of each country covered by WUI ranged from 0.1 to 17.4%, with an average of 3.5% (standard deviation 3.6%). Putting aside differing methods between the Modugno et al (2016) …”

Human-caused fire occurrence modelling in perspective: a review

“…Urban, forest and agricultural land uses coexist and intermix in these anthropic landscapes, and interfaces between them seem to favour HCF occurrence in those models that have taken them into consideration (63 interface out of 230 land-use variables) (Vilar del Hoyo et al 2011;Faivre et al 2014;Duane et al 2015;Mishra et al 2016;Modugno et al 2016;Rodrigues et al 2016). Configuration metrics have not been applied as extensively (only 13 variables) as composition or land-cover variables, but fire-prone landscapes often present high fragmentation (Martínez et al 2009;Ruiz-Mirazo et al 2012;Martínez-Fernández et al 2013) and non-complex shapes linked to the artificial boundaries set by humans (Henry and Yool 2004;Gralewicz et al 2012b;Costafreda-Aumedes et al 2013).…”

A Comparison between Spatial Econometric Models and Random Forest for Modeling Fire Occurrence

“…According to previous studies, many of which were done in forest regions, human-related predictors are critical for explaining fire occurrence on the large scales, such as in Europe and China [2][3][4][5][6]. However, few studies were done at the city scale to explain and predict of the occurrence of infrastructure fire, which may lead to a lack of efficient management for the potential fire risks hidden in a city.…”