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    倪希亮等:Estimation of Forest Biomass Patterns across Northeast China Based on Allometric Scale Relationship

    作者:来源:发布时间:2017-10-19
    Estimation of Forest Biomass Patterns across Northeast China Based on Allometric Scale Relationship
    作者:Ni, XL (Ni, Xiliang)[ 1 ] ; Cao, CX (Cao, Chunxiang)[ 1 ] ; Zhou, YK (Zhou, Yuke)[ 2 ] ; Ding, L (Ding, Lin)[ 1 ] ; Choi, SH (Choi, Sungho)[ 3 ] ; Shi, YL (Shi, Yuli)[ 4 ] ; Park, T (Park, Taejin)[ 3 ] ; Fu, X (Fu, Xiao)[ 5 ] ; Hu, H (Hu, Hong)[ 6 ] ; Wang, XJ (Wang, Xuejun)[ 7 ]
    FORESTS
    卷: 8  期: 8
    文献号: 288
    DOI: 10.3390/f8080288
    出版年: AUG 2017
    摘要
    This study develops a modeling framework for utilizing the large footprint LiDAR waveform data from the Geoscience Laser Altimeter System (GLAS) onboard NASA's Ice, Cloud, and Land Elevation Satellite (ICESat), Moderate Resolution Imaging Spectro-Radiometer (MODIS) imagery, meteorological data, and forest measurements for monitoring stocks of total biomass (including aboveground biomass and root biomass). The forest tree height models were separately used according to the artificial neural network (ANN) and the allometric scaling and resource limitation (ASRL) tree height models which can both combine the climate data and satellite data to predict forest tree heights. Based on the allometric approach, the forest aboveground biomass model was developed from the field measured aboveground biomass data and the tree heights derived from two tree height models. Then, the root biomass should scale with the aboveground biomass. To investigate whether this approach is efficient for estimating forest total biomass, we used Northeast China as the object of study. Our results generally proved that the method proposed in this study could be meaningful for forest total biomass estimation (R-2 = 0.699, RMSE = 55.86).
    通讯作者地址: Cao, CX (通讯作者)
    Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China.
    地址:
    [ 1 ] Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China
    [ 2 ] Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
    [ 3 ] Boston Univ, Dept Earth & Environm, 675 Commonwealth Ave, Boston, MA 02215 USA
    [ 4 ] Nanjing Univ Informat Sci & Technol, Sch Remote Sensing, Nanjing 210044, Jiangsu, Peoples R China
    [ 5 ] Beijing Union Univ, Coll Appl Sci & Humanities, Beijing 100083, Peoples R China
    [ 6 ] Haihe Basin Soil & Water Conservat Monitor Ctr, Tianjin 300171, Peoples R China
    [ 7 ] State Forest Adm China, Survey Planning & Design Inst, Beijing 100714, Peoples R China
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