Mapping fire risk in the Model Forest of Urbión (Spain) based on airborne LiDAR measurements José-Ramón González-Olabarria a,⇑ , Francisco Rodríguez b , Alfredo Fernández-Landa c,d , Blas Mola-Yudego e,f a Centre Tecnològic Forestal de Catalunya Ctra St. Llorenc de Munys, Km 2, ES-25280 Solsona, Spain b Cesefor Foundation, Pol. Ind. Las Casas, Calle C, Parcela 4, ES-42005 Soria, Spain c Agresta Sociedad Cooperativa, C/Numancia 1, ES-42001 Soria, Spain d Universidad Politécnica de Madrid, Ciudad Universitaria, ES-28040 Madrid, Spain e University of Eastern Finland, School of Forest Sciences, PO Box 111, FI-80101 Joensuu, Finland f Department of Crop Production Ecology, Swedish University of Agricultural Sciences (SLU), PO Box 7016, S-750 07 Uppsala, Sweden article info Article history: Received 12 April 2012 Received in revised form 29 June 2012 Accepted 30 June 2012 Keywords: Airborne LiDAR Forest inventory Fire risk assessment Mediterranean model forest abstract The present study sets a methodological framework to combine LiDAR derived data with fire behaviour models in order to assess fire risk at landscape level for forest management and planning. Two forest areas of the Model Forest in Urbión, Soria (Central Spain) were analyzed, covering 992.7 ha and 221.7 ha. The modelling phase was based in 160 field sample plots as ground data, and the LiDAR data had a density of first returns of 2 pulses/m 2 , which were used to construct 13 models for stand variables (e.g. basal area, stem volume, branch biomass). The coefficients of determination ranged from 0.167 for shrub cover, to 0.906 for dominant height. The modelled variables were used for a classification of fuel types compatible with the continuous data. The simulation phase was performed using the spatialized data on FlamMap in order to assess the potential fire behaviour resulting across the whole landscape for four scenarios of moisture and wind conditions. The results showed maps of fire intensity and prob- ability of fire occurrence, based on the simulation of 500 random ignition points, which allowed the anal- ysis of the spatial relation between the initial state and allocation of forest resources and their risk of fire. The methodology proposed, as well as the results of this research are directly applicable for operational forest planning at landscape level. Ó 2012 Elsevier B.V. All rights reserved. 1. Introduction The inclusion of fire risk into the planning of forest manage- ment is a recurrent research topic since the 1980s (e.g. Van Wag- ner, 1983; Reed and Errico, 1986). Wildfires have an obvious effect on the outcomes of forest management through post-fire tree mortality or value depreciation of surviving trees. At the same time, however, forest management has the potential of modifying fire behaviour by changing the quantity and spatial arrangement of forest fuels (Agee and Skinner, 2005; Peterson et al., 2005; Finney et al., 2007). The way of considering the risk of fire into the process of planning forest management has evolved from non-spatial ap- proaches where the effect of fire was defined as deterministic or as a stochastic quantity of timber losses, to the more recent ap- proaches were fire behaviour and its (spatially explicit) compo- nents are being considered in order to assess the extent of fire induced damage and the influence of fuel modification on fire behaviour (Bettinger, 2010). In this sense, assessing adequately the current state of the forest is one of the first steps required for planning the management of a forest area when the risk of fire is considered. The assessment re- quires collecting precise data of the amount and distribution of desirable resources and at the same time, estimates of the poten- tial threat that fire means to those resources. However, to estimate the risk of fire over a forest landscape it must be considered that fire is a spatially explicit event, and varies its behaviour depending on site-specific fuel conditions and the spatial arrangement of dif- ferent fuels (Finney, 2001). This spatial dimension, that entails information about the state of the forest and the potential behav- iour of fire across the landscape, it is required in order to choose the most effective fuel treatments, in terms of type and allocation, that would reduce the negative impact of fire on the forest (Agee et al., 2000; Finney et al., 2007). However, mapping fuel and forest stocking characteristics at a broad spatial scale is often not feasible based on direct field mea- surements. But during the last decades, the use of diverse types of remote sensors has become popular to acquire information about the continuous distribution of fuel (Chuvieco and Congalton, 1989; Arroyo et al., 2008) and forest resources at landscape level 0378-1127/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.foreco.2012.06.056 ⇑ Corresponding author. Tel.: +34 973 481752; fax: +34 973 481392. E-mail address: jr.gonzalez@ctfc.es (J.-R. González-Olabarria). Forest Ecology and Management 282 (2012) 149–156 Contents lists available at SciVerse ScienceDirect Forest Ecology and Management journal homepage: www.elsevier.com/locate/foreco