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

摘要Climate change effects tend to reinforce the fre-quency and severity of wildfires worldwide,and early detec-tion 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 acces-sibility to candidate watchtower locations)and geo-opti-mization 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 appro-priate territory for the installment of watchtowers.Terrain analysis guaranteed the independence and proximity of loca-tion options(applying spatial systematic sampling to avoid first order redundancy)across the ridges.The conjunction of the above processes yielded 654 candidate watchtower posi-tions 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 cov-erage.However,the final choice of any location scheme is subject to agency priorities and their respective financial flexibility.

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作者 Stavros Sakellariou [1] George Sfoungaris [2] Olga Christopoulou [3] 学术成果认领
作者单位 Department of Agriculture Crop Production and Rural Environment,University of Thessaly,38446 Vólos,Greece;Department of Planning and Regional Development,University of Thessaly,38334 Vólos,Greece [1] Computer Science Department,University of Crete,70013 Heraklion,Crete,Greece [2] Department of Planning and Regional Development,University of Thessaly,38334 Vólos,Greece [3]
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发布时间 2022-10-11(万方平台首次上网日期,不代表论文的发表时间)
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国际灾害风险科学学报(英文版)

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