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

doi:10.1016/j.jag.2019.01.007

	A simple and integrated approach for fire severity assessment using bi-temporal airborne LiDAR data
	Hu, Tianyu ; Ma, Qin 1,2; Su, Yanjun 1,2; Battles, John J.; Collins, Brandon M.; Stephens, Scott L.; Kelly, Maggi 3,4; Guo, Qinghua1,2,7
	2019
发表期刊	INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
ISSN	0303-2434
卷号	78 页码:25-38
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.
关键词	Fire severity Fire type Tree canopy Airborne LiDAR Profile area change
学科领域	Remote Sensing
DOI	10.1016/j.jag.2019.01.007
收录类别	SCI
语种	英语
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
WOS记录号	WOS:000463131700003
出版者	ELSEVIER
文献子类	Article
出版地	AMSTERDAM
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]
作者邮箱	ysu@ibcas.ac.cn
引用统计	被引频次：26[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	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.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China 2.Univ Calif Merced, Sierra Nevada Res Inst, Merced, CA USA 3.Univ Calif Merced, Sch Engn, Merced, CA USA 4.Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA 5.Univ Calif Davis, Div Agr & Nat Resources, Davis, CA 95616 USA 6.Collins, Brandon M.] US Forest Serv, USDA, Pacific Southwest Res Stn, Davis, CA 95418 USA 7.Collins, Brandon M.] Univ Calif Berkeley, Ctr Fire Res & Outreach, Berkeley, CA 94720 USA 8.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China
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.

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