IGSNRR OpenIR
Estimating woody aboveground biomass in an area of agroforestry using airborne light detection and ranging and compact airborne spectrographic imager hyperspectral data: individual tree analysis incorporating tree species information
Wang, Zhihui1,2,3,4; Liu, Liangyun1; Peng, Dailiang1; Liu, Xinjie1; Zhang, Su1; Wang, Yingjie1
2016-07-19
Source PublicationJOURNAL OF APPLIED REMOTE SENSING
ISSN1931-3195
Volume10Pages:20
Corresponding AuthorLiu, Liangyun(liuly@radi.ac.cn)
AbstractUntil now, there have been only a few studies that have made estimates of the woody aboveground biomass (AGB) in an area of agroforestry using remote sensing technology. The woody AGB density was estimated using individual tree analysis (ITA) that incorporated tree species information using a combination of airborne light detection and ranging (LiDAR) and compact airborne spectrographic imagery acquired over a typical agroforestry in northwestern China. First, a series of improved LiDAR processing algorithms was applied to achieve individual tree segmentation, and accurate plot-level canopy heights and crown diameters were obtained. The individual tree species were then successfully classified using both spectral and shape characteristics with an overall accuracy of 0.97 and a kappa coefficient of 0.85. Finally, the tree-level AGB (kg) was estimated based on the ITA; the AGB density (Mg/ha) was then upscaled based on the tree-level AGB values. It is concluded that, compared with the commonly used area-based method combining LiDAR and spectral metrics [root mean square error (RMSE) = 19.58 Mg/ha], the ITA method performs better at estimating AGB density (RMSE = 10.56 Mg/ha). The tree species information also improved the accuracy of the AGB estimation even though the species are not well diversified in this study area. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Keywordagroforestry woody aboveground biomass individual tree analysis light detection and ranging tree species
DOI10.1117/1.JRS.10.036007
WOS KeywordSMALL-FOOTPRINT LIDAR ; LASER SCANNER DATA ; CARBON SEQUESTRATION ; FOREST STRUCTURE ; TROPICAL FOREST ; CLASSIFICATION ; MODEL ; ENVIRONMENT ; ECOSYSTEM ; HEIGHTS
Indexed BySCI
Language英语
Funding Projecthigh-resolution earth observation project of China[30-Y20A29-9003-15/17] ; National Natural Science Foundation of China[41571423] ; Innovative Scientists and Technicians Troop Construction Projects of Henan Province[162101510004]
Funding Organizationhigh-resolution earth observation project of China ; National Natural Science Foundation of China ; Innovative Scientists and Technicians Troop Construction Projects of Henan Province
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS SubjectEnvironmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS IDWOS:000389723900001
PublisherSPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/65444
Collection中国科学院地理科学与资源研究所
Corresponding AuthorLiu, Liangyun
Affiliation1.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
2.Minist Water Resources, Yellow River Inst Hydraul Res, Yellow River Conservancy Commiss, Zhengzhou 450003, Peoples R China
3.Minist Water Resources, Key Lab Loess Plateau Soil Eros & Water Proc & Co, Zhengzhou 450003, Peoples R China
4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
Recommended Citation
GB/T 7714
Wang, Zhihui,Liu, Liangyun,Peng, Dailiang,et al. Estimating woody aboveground biomass in an area of agroforestry using airborne light detection and ranging and compact airborne spectrographic imager hyperspectral data: individual tree analysis incorporating tree species information[J]. JOURNAL OF APPLIED REMOTE SENSING,2016,10:20.
APA Wang, Zhihui,Liu, Liangyun,Peng, Dailiang,Liu, Xinjie,Zhang, Su,&Wang, Yingjie.(2016).Estimating woody aboveground biomass in an area of agroforestry using airborne light detection and ranging and compact airborne spectrographic imager hyperspectral data: individual tree analysis incorporating tree species information.JOURNAL OF APPLIED REMOTE SENSING,10,20.
MLA Wang, Zhihui,et al."Estimating woody aboveground biomass in an area of agroforestry using airborne light detection and ranging and compact airborne spectrographic imager hyperspectral data: individual tree analysis incorporating tree species information".JOURNAL OF APPLIED REMOTE SENSING 10(2016):20.
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