干旱区生态环境知识资源中心(Arid): Remote sensing delineation of wildfire spatial extents and post-fire recovery along a semi-arid climate gradient

Arid

DOI	10.1016/j.ecoinf.2023.102304
	Remote sensing delineation of wildfire spatial extents and post-fire recovery along a semi-arid climate gradient
	Liu, Wenjie; Guan, Huade; Hesp, Patrick A.; Batelaan, Okke
通讯作者	Guan, HD
来源期刊	ECOLOGICAL INFORMATICS
ISSN	1574-9541
EISSN	1878-0512
出版年	2023
卷号	78
英文摘要	Understanding the wildfire extent and post-fire vegetation recovery is critical for fire and forest management. Remote sensing imagery is widely used in wildfire detection because it provides continuous and large-scale surface monitoring capability. In this study, we apply and evaluate the performance of the LandTrendr algorithm in wildfire detection across a semi-arid climate region with a marked precipitation gradient. The aims are to compare the performance of four spectral indices for the burned areas and post-fire recovery detection for different climate conditions and investigate the relationship between suitable model parameters and climate conditions. The results show that NDVI outperforms other indices, including NBR, in burned area detection for drier areas (annual precipitation <400 mm). Disturbance signal-to-noise ratio can serve as an indicator for suitable index selection for semi-arid areas. Although the performance in the detection of burned pixels varies among different indices, they are all suitable for delineating post-fire recovery except for the wet site (annual precipitation of 575 mm) where NBR displays the best performance. Parameter optimization results along the climate gradient show that climate conditions have a significant impact on suitable parameter selection. These findings provide guidance on vegetation wildfire detection in arid and semi-arid climates to support wildfire risk and forestry management.
英文关键词	Wildfire Change detection LandTrendr Post-fire vegetation recovery
类型	Article
语种	英语
开放获取类型	hybrid
收录类别	SCI-E
WOS记录号	WOS:001082329100001
WOS关键词	FOREST DISTURBANCE ; TIME-SERIES ; TEMPORAL PATTERNS ; DETECTING TRENDS ; FIRE SEVERITY ; BURN SEVERITY ; LANDSAT TM ; AREA ; LANDTRENDR ; CLASSIFICATION
WOS类目	Ecology
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395997
推荐引用方式 GB/T 7714	Liu, Wenjie,Guan, Huade,Hesp, Patrick A.,et al. Remote sensing delineation of wildfire spatial extents and post-fire recovery along a semi-arid climate gradient[J],2023,78.
APA	Liu, Wenjie,Guan, Huade,Hesp, Patrick A.,&Batelaan, Okke.(2023).Remote sensing delineation of wildfire spatial extents and post-fire recovery along a semi-arid climate gradient.ECOLOGICAL INFORMATICS,78.
MLA	Liu, Wenjie,et al."Remote sensing delineation of wildfire spatial extents and post-fire recovery along a semi-arid climate gradient".ECOLOGICAL INFORMATICS 78(2023).