Volume 13 Issue 4
Aug.  2022
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Stavros Sakellariou, George Sfoungaris, Olga Christopoulou. Territorial Resilience Through Visibility Analysis for Immediate Detection of Wildfires Integrating Fire Susceptibility, Geographical Features, and Optimization Methods[J]. International Journal of Disaster Risk Science, 2022, 13(4): 621-635. doi: 10.1007/s13753-022-00433-2
Citation: Stavros Sakellariou, George Sfoungaris, Olga Christopoulou. Territorial Resilience Through Visibility Analysis for Immediate Detection of Wildfires Integrating Fire Susceptibility, Geographical Features, and Optimization Methods[J]. International Journal of Disaster Risk Science, 2022, 13(4): 621-635. doi: 10.1007/s13753-022-00433-2

Territorial Resilience Through Visibility Analysis for Immediate Detection of Wildfires Integrating Fire Susceptibility, Geographical Features, and Optimization Methods

doi: 10.1007/s13753-022-00433-2
Funds:

This scientific publication took place within the framework of the project “Grant for Post-Doctoral Research” of the University of Thessaly, which is being implemented in the University of Thessaly and financed by the Stavros Niarchos Foundation. In addition, we would like to thank the anonymous reviewers and the Editors for their fruitful comments that led us to the improvement of the paper.

  • Available Online: 2022-09-09
  • Climate change effects tend to reinforce the frequency and severity of wildfires worldwide, and early detection of wildfire events is considered of crucial importance. The primary aim of this study was the spatial optimization of fire resources (that is, watchtowers) considering the interplay of geographical features (that is, simulated burn probability to delimit fire vulnerability; topography effects; and accessibility to candidate watchtower locations) and geo-optimization techniques (exact programming methods) to find both an effective and financially feasible solution in terms of visibility coverage in Chalkidiki Prefecture of northern Greece. The integration of all geographical features through the Analytical Hierarchy Process indicated the most appropriate territory for the installment of watchtowers. Terrain analysis guaranteed the independence and proximity of location options (applying spatial systematic sampling to avoid first order redundancy) across the ridges. The conjunction of the above processes yielded 654 candidate watchtower positions in 151,890 ha of forests. The algorithm was designed to maximize the joint visible area and simultaneously minimize the number of candidate locations and overlapping effects (avoiding second order redundancy). The results indicate four differentiated location options in the study area: (1) 75 locations can cover 90% of the forests (maximum visible area); (2) 47 locations can cover 85% of the forests; (3) 31 locations can cover 80.2% of the forests; and (4) 16 locations can cover 70.6% of the forests. The last option is an efficient solution because it covers about 71% of the forests with just half the number of watchtowers that would be required for the third option with only about 10% additional forest coverage. However, the final choice of any location scheme is subject to agency priorities and their respective financial flexibility.
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