Spatial planning of fire-agency stations as a function of wildfire likelihood in Thasos, Greece

Sci Total Environ. 2020 Aug 10:729:139004. doi: 10.1016/j.scitotenv.2020.139004. Epub 2020 Apr 27.

Abstract

Even though wildfires constitute a natural phenomenon, they may have severe implications with respect to the socioeconomic structure of the affected population and the ecological wealth of a territory, especially when they burn under high intensities. Timing of the initial attack is thus crucial to fire control in areas that fires are considered to be under high threat of burning. The aim of this paper is to investigate the combined use of simulation modeling and spatial optimization to assess the pre-positioning of fire-management resources on a small Greek island, Thasos, based on the current and desired fire agency capabilities, maximization of environmental protection, and rationalization of financial resources. The estimation of burn probability (BP) depicted specific areas of high fire hazard in the southern, central, and western part of the island, where essential preventive measures should be undertaken. Based on this result, BP was then used as a primary input for the assessment of optimal locations of fire operation agencies in order to achieve the maximal coverage under certain (already available) and minimum number of fire-fighting vehicles in different time windows. The results generated three differentiated optimal location schemes [8 available vehicles within either 10 (immediate response time) or 31 min (average response time) with the current fire resources; 19 and 2 required vehicles within 10 and 31 min, respectively, based on a minimum number of fire resources]. This type of information enables us to propose a relocation of the current fire agency in a southern town of the island. The flexibility and interaction of the models provide a framework for appropriate decision making under a set of political and financial constraints.

Keywords: Burn probability; Fire management; Forest fires; Simulation modeling; Spatial optimization; Thasos island.