DettoAsnerMuller-LandauEtAl2015

Référence

Detto, M., Asner, G.P., Muller-Landau, H.C. and Sonnentag, O. (2015) Spatial variability in tropical forest leaf area density from multireturn lidar and modeling. Journal of Geophysical Research: Biogeosciences, 120(2):294-309. (Scopus )

Résumé

Leaf area index and leaf area density profiles are key variables for upscaling from leaves to ecosystems yet are difficult to measure well in dense and tall forest canopies. We present a new model to estimate leaf area density profiles from discrete multireturn data derived by airborne waveform light detection and ranging (lidar), a model based on stochastic radiative transfer theory. We tested the method on simulated ray tracing data for highly clumped forest canopies, both vertically homogenous and vertically inhomogeneous. Our method was able to reproduce simulated vertical foliage profiles with small errors and predictable biases in dense canopies (leaf area index = 6) including layers below densely foliated upper canopies. As a case study, we then applied the method to real multireturn airborne lidar data for a 50 ha plot of moist tropical forest on Barro Colorado Island, Panama. The method is suitable for estimating foliage profiles in a complex tropical forest, which opens new avenues for analyses of spatial and temporal variations in foliage distributions. Key Points A new method for estimating leaf area from multireturn lidar in complex forest Simulation data sets to test the inversion algorithm A case study of a moist tropical forest ©2015. American Geophysical Union. All Rights Reserved.

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@ARTICLE { DettoAsnerMuller-LandauEtAl2015,
    AUTHOR = { Detto, M. and Asner, G.P. and Muller-Landau, H.C. and Sonnentag, O. },
    TITLE = { Spatial variability in tropical forest leaf area density from multireturn lidar and modeling },
    JOURNAL = { Journal of Geophysical Research: Biogeosciences },
    YEAR = { 2015 },
    VOLUME = { 120 },
    NUMBER = { 2 },
    PAGES = { 294-309 },
    NOTE = { cited By 14 },
    ABSTRACT = { Leaf area index and leaf area density profiles are key variables for upscaling from leaves to ecosystems yet are difficult to measure well in dense and tall forest canopies. We present a new model to estimate leaf area density profiles from discrete multireturn data derived by airborne waveform light detection and ranging (lidar), a model based on stochastic radiative transfer theory. We tested the method on simulated ray tracing data for highly clumped forest canopies, both vertically homogenous and vertically inhomogeneous. Our method was able to reproduce simulated vertical foliage profiles with small errors and predictable biases in dense canopies (leaf area index = 6) including layers below densely foliated upper canopies. As a case study, we then applied the method to real multireturn airborne lidar data for a 50 ha plot of moist tropical forest on Barro Colorado Island, Panama. The method is suitable for estimating foliage profiles in a complex tropical forest, which opens new avenues for analyses of spatial and temporal variations in foliage distributions. Key Points A new method for estimating leaf area from multireturn lidar in complex forest Simulation data sets to test the inversion algorithm A case study of a moist tropical forest ©2015. American Geophysical Union. All Rights Reserved. },
    AFFILIATION = { Smithsonian Tropical Research Institute, Panama City, Panama; Carnegie Institution for Science, Palo Alto, CA, United States; Département de Géographie, Université de Montréal, Montréal, QC, Canada },
    AUTHOR_KEYWORDS = { complex forest; leaf area density; leaf area index; multireturn lidar; tropical forest; waveform lidar },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1002/2014JG002774 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028157912&doi=10.1002%2f2014JG002774&partnerID=40&md5=596c0b0d98830eb6a58d1fb7cd66a5d5 },
}

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