A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data

doi:10.1016/j.jag.2019.01.007

CORC > 植物研究所 > 中国科学院植物研究所 > 植被与环境变化国家重点实验室

	A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data
	Hu, Tianyu ; Ma, Qin 1,6; Su, Yanjun 1,6; Battles, John J.; Collins, Brandon M.; Stephens, Scott L.; Kelly, Maggi 4,5; Guo, Qinghua 1,6,8
刊名	INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
	2019
卷号	78 页码:25-38
关键词	Fire severity Fire type Tree canopy Airborne LiDAR Profile area change
ISSN号	0303-2434
DOI	10.1016/j.jag.2019.01.007
文献子类	Article
英文摘要	This study proposes a new method (profile area change, PAC) to quantify fire-induced forest structural changes at the individual tree and clump of trees scales using pre- and post-fire LiDAR data. The PAC measures the difference in profile area summarized from pre- and post-fire LiDAR points. We applied the PAC method to assess the effects of the 2013 American Fire in the Sierra Nevada, California, USA. Our LiDAR PAC metrics were compared to changes in commonly used LiDAR-derived canopy cover and tree height metrics at tree level, and to Landsat-8 imagery-derived relative differenced normalized burn ratio (RdNBR) at the 30m pixel level. A quantitative validation using field measured changes in basal area and leaf area index (LAI) confirmed that correlations between PAC metrics and field measurements (R-2 >= 0.67) were significantly higher than those from canopy cover or tree height metrics (R-2 <= 0.43), and much stronger than that from RdNBR (R-2 <= 0.26). The PAC metrics can also be used to infer the extent of tree canopy disturbance caused by fire, based on whether the majority of biomass loss occurred above or below the tree crown base height. Mapping of canopy disturbance indicated that over half (57.0%) of the American Fire region had tree canopy loss from fire, 22.5% of trees had sub-canopy loss, while the remaining area had no detectable tree canopy change. Overall, the LiDAR PAC metric, as a simple and integrated method, demonstrated promising potential in characterizing fine-grained changes in forest structure. The method can be beneficial for forest managers in evaluating fire-induced environmental and economic losses, and provide useful information for forest restoration design.
学科主题	Remote Sensing
出版地	AMSTERDAM
WOS关键词	MIXED-CONIFER FORESTS ; LANDSAT TIME-SERIES ; BURN SEVERITY ; MULTITEMPORAL LIDAR ; SIERRA-NEVADA ; BIOMASS ESTIMATION ; INDIVIDUAL TREES ; BOREAL ; METRICS ; CLASSIFICATION
WOS研究方向	Remote Sensing
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000463131700003
资助机构	Strategic Priority Research Program of Chinese Academy of SciencesChinese Academy of Sciences [XDA19050401] ; CAS Pioneer Hundred Talents Program ; USDA Forest Service Region 5 ; USDA Forest Service Pacific Southwest Research StationUnited States Department of Agriculture (USDA)United States Forest Service ; US Fish and Wildlife ServiceUS Fish & Wildlife Service ; California Department of Water Resources ; California Department of Fish and Wildlife ; California Department of Forestry and Fire Protection ; Sierra Nevada Conservancy ; National Science Foundation Division of Environmental Biology AwardNational Science Foundation (NSF) [1450144]
内容类型	期刊论文
源URL	[http://ir.ibcas.ac.cn/handle/2S10CLM1/19429]
专题	植被与环境变化国家重点实验室
作者单位	1.Univ Calif Merced, Sierra Nevada Res Inst, Merced, CA USA 2.Collins, Brandon M.] US Forest Serv, USDA, Pacific Southwest Res Stn, Davis, CA 95418 USA 3.Univ Calif Davis, Div Agr & Nat Resources, Davis, CA 95616 USA 4.Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA 5.Univ Calif Merced, Sch Engn, Merced, CA USA 6.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China 7.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China 8.Collins, Brandon M.] Univ Calif Berkeley, Ctr Fire Res & Outreach, Berkeley, CA 94720 USA
推荐引用方式 GB/T 7714	Hu, Tianyu,Ma, Qin,Su, Yanjun,et al. A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2019,78:25-38.
APA	Hu, Tianyu.,Ma, Qin.,Su, Yanjun.,Battles, John J..,Collins, Brandon M..,...&Guo, Qinghua.(2019).A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,78,25-38.
MLA	Hu, Tianyu,et al."A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 78(2019):25-38.