Downloads provided by UsageCounts
handle: 10261/293765 , 10459.1/69833
The forest area burnt annually in the European Mediterranean region has more than doubled since the 1970s. In these forests, the main preventive action consists of forest compartmentalization by fuel break networks, which entail high costs and sometimes significant negative impacts. While many studies look at public preferences for fire suppression, this study analyses the heterogeneity of social preferences for fire prevention. The visual characteristics of fire prevention structures are very familiar to respondents, but their management is unfamiliar, which raises specific attention in terms of analysing preference heterogeneity. A random parameter logit model revealed large heterogeneity and preference for traditional heavy machinery, maintaining linear unshaded fuel breaks at a high density. A latent class model showed that this may be reflected by a third of the population preferring lighter machinery and shaded irregular fuel breaks; a quarter of the population not treating the budget constraint as limiting, another quarter only being worried about the area burnt and the remaining group being against everything. Finally, a discrete mixture model revealed extreme preference patterns for the density of fuel breaks. These results are important for designing fire prevention policies that are efficient and acceptable by the population. © 2014 Elsevier B.V.
Peer reviewed
Forest fires, Discrete mixture model, Fuel breaks, Choice modelling, Random parameter logit, Latent class model, Heterogeneity
Forest fires, Discrete mixture model, Fuel breaks, Choice modelling, Random parameter logit, Latent class model, Heterogeneity
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 41 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 67 | |
| downloads | 20 |

Views provided by UsageCounts
Downloads provided by UsageCounts