GIS-based forest fire risk determination for Milas district, Turkey

被引:38
作者
Cetin, Mehmet [1 ]
Pekkan, Ozge Isik [2 ]
Kavlak, Mehtap Ozenen [2 ]
Atmaca, Ilker [3 ]
Nasery, Suhrabuddin [2 ]
Derakhshandeh, Masoud [4 ]
Cabuk, Saye Nihan [5 ]
机构
[1] Ondokuz Mayis Univ, Fac Architecture, Dept City & Reg Planning, Samsun, Turkey
[2] Eskisehir Tech Univ, Inst Grad Programs, Dept Remote Sensing & Geog Informat Syst, Iki Eylul Campus, TR-26555 Tepebasi, Eskisehir, Turkey
[3] Yozgat Bozok Univ, Fac Engn & Architecture, Dept City & Reg Planning, Erdogan Akdag Campus, TR-66900 Yozgat, Turkey
[4] Istanbul Gelisim Univ, Fac Architecture & Engn, Dept Civil Engn, TR-34310 Istanbul, Turkey
[5] Eskisehir Tech Univ, Dept Geodesy & Geog Informat Technol, Inst Earth & Space Sci, Iki Eylul Kampusu, TR-26555 Tepebasi, Eskisehir, Turkey
关键词
Burn area index; Forest fire; GIS; Normalized burn ratio index; Risk assessment; WEATHER; SLOPE; INDEX; PATTERNS; IGNITION; SPREAD;
D O I
10.1007/s11069-022-05601-7
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Forest fires are highly destructive phenomena in both ecological and economic terms. Therefore, it is significant to develop measures to detect and mitigate them. In this study, the forest fire risk map of the Milas district of Turkey was studied using geographical information systems and remote sensing methods. In the first part of the study, the forest fire risk map of the area was developed via a weighted overlay technique with analysis of stand characteristics, topographic features, distance from intermittent streams and built-up environment. According to the resulting forest fire risk map, extremely low-, low-, medium-, high- and extremely high-risk classes covered 0%, 0.5%, 65%, 30% and 0.5% of the forested areas in Milas district of Turkey, respectively. In the second part, the location of a major forest fire, which took place in 2007 in the study area, was determined using the normalized difference vegetation index, the normalized burn ratio, and the burn area index. When compared with the forest fire risk map, it was revealed that 45% of the burned areas in 2007 fell into the high-risk class, while 51% of it was from the extremely high-risk zones. Moreover, the forest risk map was compared with eleven forest fire cases between 2013 and 2019. The results show that eight of these fires took place in high-risk territories. According to these results, it was concluded that the created risk map coincides with the fire incidents.
引用
收藏
页码:2299 / 2320
页数:22
相关论文
共 76 条
[1]   Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques [J].
Adab, Hamed ;
Kanniah, Kasturi Devi ;
Solaimani, Karim .
NATURAL HAZARDS, 2013, 65 (03) :1723-1743
[2]   GIS-BASED MULTI-CRITERIA DECISION ANALYSIS FOR FOREST FIRE RISK MAPPING [J].
Akay, A. E. ;
Erdogan, A. .
4TH INTERNATIONAL GEOADVANCES WORKSHOP - GEOADVANCES 2017: ISPRS WORKSHOP ON MULTI-DIMENSIONAL & MULTI-SCALE SPATIAL DATA MODELING, 2017, 4-4 (W4) :25-30
[3]  
Akay A. E., 2019, EUR J FOR ENG, V5, P25, DOI [10.33904/ejfe.579075, DOI 10.33904/EJFE.579075]
[4]  
Akbulak C., 2018, J HUM SCI, V15, P2127, DOI DOI 10.14687/JHS.V15I4.5491
[5]   Assessment of forest fire vulnerability zones in Missouri, United States of America [J].
Akinola, O. V. ;
Adegoke, J. .
INTERNATIONAL JOURNAL OF SUSTAINABLE DEVELOPMENT AND WORLD ECOLOGY, 2019, 26 (03) :251-257
[6]  
Akkas M, 2008, TEKNIK BULTEN, V36
[7]   Fire weather index system components for large fires in the Canadian boreal forest [J].
Amiro, BD ;
Logan, KA ;
Wotton, BM ;
Flannigan, MD ;
Todd, JB ;
Stocks, BJ ;
Martell, DL .
INTERNATIONAL JOURNAL OF WILDLAND FIRE, 2004, 13 (04) :391-400
[8]  
[Anonymous], 2010, GEN TECH REP
[9]  
[Anonymous], 2019, Statistical approaches for landslide susceptibility assessment and prediction
[10]   Optimizing watchtower locations for forest fire monitoring using location models [J].
Bao, Shitai ;
Xiao, Ningchuan ;
Lai, Zehui ;
Zhang, Heyuan ;
Kim, Changjoo .
FIRE SAFETY JOURNAL, 2015, 71 :100-109