Territorial Resilience Through Visibility Analysis for Immediate Detection of Wildfires Integrating Fire Susceptibility, Geographical Features, and Optimization Methods
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 geo...
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Published in | International journal of disaster risk science Vol. 13; no. 4; pp. 621 - 635 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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Singapore
Springer Nature Singapore
01.08.2022
Springer Springer Nature B.V |
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Online Access | Get full text |
ISSN | 2095-0055 2192-6395 |
DOI | 10.1007/s13753-022-00433-2 |
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Abstract | 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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AbstractList | 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. |
Audience | Academic |
Author | Sfoungaris, George Sakellariou, Stavros Christopoulou, Olga |
Author_xml | – sequence: 1 givenname: Stavros surname: Sakellariou fullname: Sakellariou, Stavros email: stasakel@gmail.com organization: Department of Agriculture Crop Production and Rural Environment, University of Thessaly, Department of Planning and Regional Development, University of Thessaly – sequence: 2 givenname: George surname: Sfoungaris fullname: Sfoungaris, George organization: Computer Science Department, University of Crete – sequence: 3 givenname: Olga surname: Christopoulou fullname: Christopoulou, Olga organization: Department of Planning and Regional Development, University of Thessaly |
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Cites_doi | 10.3390/su11247166 10.3390/s20175014 10.1080/17538947.2016.1207718 10.1080/2150704X.2017.1350303 10.4018/IJAEIS.2017100101 10.1016/j.scitotenv.2018.11.038 10.1016/j.eswa.2019.112975 10.1080/13658816.2019.1664743 10.5194/bg-11-7305-2014 10.3390/s18030712 10.1029/2019GL083699 10.1007/3-540-35589-8_52 10.1007/978-3-030-55563-4_4 10.1016/j.scitotenv.2020.139004 10.1007/s11676-018-0666-x 10.1109/HIS.2010.5600013 10.5194/nhess-18-847-2018 10.1007/978-3-642-56094-1_9 10.3390/f12010005 10.1016/j.envsoft.2013.04.004 10.1139/cjfr-2019-0413 10.14358/PERS.69.8.881 10.1016/j.scitotenv.2020.139561 10.1080/17477891.2019.1628696 10.1016/j.landusepol.2019.104206 10.1155/2014/597368 10.1038/s41598-019-46362-x 10.1016/j.ijdrr.2020.101479 10.1016/j.scitotenv.2016.03.231 10.1016/0377-2217(90)90057-I 10.1088/1748-9326/aa7e6e 10.1007/s11069-012-0495-8 10.1016/j.ijdrr.2022.103129 10.1016/j.still.2017.12.005 10.1016/j.cageo.2004.07.008 10.1007/s10661-017-6008-1 10.1016/j.firesaf.2014.11.016 |
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Title | Territorial Resilience Through Visibility Analysis for Immediate Detection of Wildfires Integrating Fire Susceptibility, Geographical Features, and Optimization Methods |
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