Comparison of Canopy Cover Estimations From Airborne LiDAR, Aerial Imagery, and Satellite Imagery
Ma, Qin; Su, Yanjun; Guo, Qinghua1
刊名IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
2017
卷号10期号:9页码:4225-4236
关键词Canopy cover light detection and ranging (LiDAR) National Agricultural Imagery Program WorldView-2
ISSN号1939-1404
DOI10.1093/pcp/pcw204
文献子类Article
英文摘要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.
学科主题Plant Sciences ; Cell Biology
电子版国际标准刊号2151-1535
出版地PISCATAWAY
WOS关键词SMALL-FOOTPRINT ; ABOVEGROUND BIOMASS ; INDIVIDUAL TREES ; SAMPLING DENSITY ; PULSE DENSITY ; POINT DENSITY ; FOREST ; LASER ; METRICS ; PARAMETERS
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000397159200001
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
内容类型期刊论文
源URL[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
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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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