气候变化领域集成服务门户(CCPortal): Remote sensing and GIS-based inventory and analysis of the unprecedented 2021 forest fires in Türkiye's history

CCPortal

DOI	10.1007/s11069-024-06622-0
	Remote sensing and GIS-based inventory and analysis of the unprecedented 2021 forest fires in Türkiye's history
	Eker, Remzi; Cinar, Tunahan; Baysal, Ismail; Aydin, Abdurrahim
发表日期	2024
ISSN	0921-030X
EISSN	1573-0840
英文摘要	In the summer of 2021, T & uuml;rkiye experienced unprecedented forest fire events. Throughout that fire season, a total of 291 fire incidents, covering an area of 202,361 hectares, dominated the public agenda. This study aimed to document and analyze the 30 large fires (affecting over 100 hectares) of 2021 using remote sensing and GIS techniques. A comprehensive fire database was established, encompassing information on burned areas, fire severity, and fuel types, determined from forest-stand types and topographical properties including slope, elevation, and aspect (in eight directions). Sentinel-2 satellite images were utilized to calculate dNBR values for assessing fire severity, analyzed in the Google Earth Engine platform. Three GIS-integrated Python scripts were developed to construct the fire database. In total, 164,658 hectares were affected by these large fires, occurring solely in three regions of T & uuml;rkiye: the Mediterranean, Aegean, and Eastern Anatolian. The majority of the burned area was situated in the Mediterranean region (59%), with only 3% in Eastern Anatolia. The burned areas ranged from a minimum of 150 hectares to a maximum of 58,798 hectares. Additionally, 679 hectares of residential areas and 22,601 hectares of agricultural land were impacted by the fire events. For each fire, 21 fuel types and their distribution were determined. The most prevalent fire-prone class, Pure Turkish pine species (Pr-& Ccedil;z), accounted for 59.56% of the total affected area (99,516 hectares). Another significant fire-prone pine species, the Pure Black pine species (Pr-& Ccedil;k), covered 7.67% (12,811 hectares) of the affected area. Fuel types were evaluated by considering both forest-stand development stages and canopy closure. Regarding forest-stand development stages, the largest area percentage burned belonged to the Mature class (26.48%).
英文关键词	Forest fires; Fire severity; GEE platform; GIS; Remote sensing; T & uuml;rkiye
语种	英语
WOS研究方向	Geology ; Meteorology & Atmospheric Sciences ; Water Resources
WOS类目	Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences ; Water Resources
WOS记录号	WOS:001209547500001
来源期刊	NATURAL HAZARDS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/303188
作者单位	Izmir Katip Celebi University; Duzce University
推荐引用方式 GB/T 7714	Eker, Remzi,Cinar, Tunahan,Baysal, Ismail,et al. Remote sensing and GIS-based inventory and analysis of the unprecedented 2021 forest fires in Türkiye's history[J],2024.
APA	Eker, Remzi,Cinar, Tunahan,Baysal, Ismail,&Aydin, Abdurrahim.(2024).Remote sensing and GIS-based inventory and analysis of the unprecedented 2021 forest fires in Türkiye's history.NATURAL HAZARDS.
MLA	Eker, Remzi,et al."Remote sensing and GIS-based inventory and analysis of the unprecedented 2021 forest fires in Türkiye's history".NATURAL HAZARDS (2024).