Comparison of Canopy Cover Estimations From Airborne LiDAR, Aerial Imagery, and Satellite Imagery

doi:10.1093/pcp/pcw204

	Comparison of Canopy Cover Estimations From Airborne LiDAR, Aerial Imagery, and Satellite Imagery
	Ma, Qin ; Su, Yanjun ; Guo, Qinghua1
	2017
发表期刊	IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
ISSN	1939-1404
卷号	10 期号:9 页码:4225-4236
摘要	Canopy cover is an important forest structure parameter for many applications in ecology, hydrology, and forest management. Light detection and ranging (LiDAR) is a promising tool for estimating canopy cover because it can penetrate forest canopy. Various algorithms have been developed to calculate canopy cover from LiDAR data. However, little attention was paid to evaluating how different factors, such as estimation algorithm, LiDAR point density and scan angle, influence canopy cover estimates; and how LiDAR-derived canopy cover differs from estimates using traditional methods, such as field measurements, aerial and satellite imagery. In this study, we systematically compared canopy cover estimations from LiDAR data, quick field measurements, aerial imagery, and satellite imagery using different algorithms. The results show that LiDAR-derived canopy cover estimates are marginally influenced by the estimation algorithms. LiDAR data with a point density of 1 point/m(2) can generate comparable canopy cover estimates to data with a higher density. The uncertainty of canopy cover estimates from LiDAR data increased drastically as scan angles exceed 12 degrees. Plot-level canopy cover estimates derived from quick field measurements do not have strong correlation with LiDAR-derived estimations. Both the aerial imagery-derived and satellite imagery-derived canopy cover estimates are comparable to LiDAR-derived canopy cover estimates at the forest stand scale, but tend to be overestimated in sparse forests and be underestimated in dense forests, particularly for the aerial imagery-derived estimates. The results from this study can provide practical guidance for the selection of data sources, sampling schemes, and estimation methods in regional canopy cover mapping.
关键词	Canopy cover light detection and ranging (LiDAR) National Agricultural Imagery Program WorldView-2
学科领域	Plant Sciences ; Cell Biology
DOI	10.1093/pcp/pcw204
收录类别	SCI
语种	英语
WOS关键词	SMALL-FOOTPRINT ; ABOVEGROUND BIOMASS ; INDIVIDUAL TREES ; SAMPLING DENSITY ; PULSE DENSITY ; POINT DENSITY ; FOREST ; LASER ; METRICS ; PARAMETERS
WOS记录号	WOS:000397159200001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Special Issue	SI
文献子类	Article
出版地	PISCATAWAY
EISSN	2151-1535
资助机构	National Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41471363, 31270563] ; National Science FoundationNational Science Foundation (NSF) [DBI 1356077] ; US Department of Agriculture Forest Service Pacific Southwest Research StationUnited States Department of Agriculture (USDA)United States Forest Service
作者邮箱	qma@ucmerced.edu ; ysu3@ucmerced.edu ; guo.qinghua@gmail.com
作品OA属性	Bronze
引用统计	被引频次：11[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/2S10CLM1/22156
专题	植被与环境变化国家重点实验室
作者单位	1.Univ Calif Merced, Sch Engn, Sierra Nevada Res Inst, Merced, CA 95343 USA 2.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
推荐引用方式 GB/T 7714	Ma, Qin,Su, Yanjun,Guo, Qinghua. Comparison of Canopy Cover Estimations From Airborne LiDAR, Aerial Imagery, and Satellite Imagery[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2017,10(9):4225-4236.
APA	Ma, Qin,Su, Yanjun,&Guo, Qinghua.(2017).Comparison of Canopy Cover Estimations From Airborne LiDAR, Aerial Imagery, and Satellite Imagery.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,10(9),4225-4236.
MLA	Ma, Qin,et al."Comparison of Canopy Cover Estimations From Airborne LiDAR, Aerial Imagery, and Satellite Imagery".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 10.9(2017):4225-4236.

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