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    Author(s): Carlos Alberto Silva; Andrew Thomas Hudak; Carine Klauberg; Lee Alexandre Vierling; Carlos Gonzalez‑Benecke; Samuel de Padua Chaves Carvalho; Luiz Carlos Estraviz Rodriguez; Adrian Cardil
    Date: 2017
    Source: Carbon Balance Manage. 12: 13.
    Publication Series: Scientific Journal (JRNL)
    Station: Rocky Mountain Research Station
    PDF: View PDF  (5.0 MB)

    Description

    LiDAR measurements can be used to predict and map AGC across variable-age Eucalyptus plantations with adequate levels of precision and accuracy using 5 pulses m− 2 and a grid cell size of 5 m. The promising results for AGC modeling in this study will allow for greater confidence in comparing AGC estimates with varying LiDAR sampling densities for Eucalyptus plantations and assist in decision making towards more cost effective and efficient forest inventory.

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    Citation

    Silva, Carlos Alberto; Hudak, Andrew Thomas; Klauberg, Carine; Vierling, Lee Alexandre; Gonzalez‑Benecke, Carlos; Carvalho, Samuel de Padua Chaves; Rodriguez, Luiz Carlos Estraviz; Cardil, Adrian. 2017. Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast‑growing Eucalyptus forest plantation using airborne LiDAR data. Carbon Balance Manage. 12: 13.

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    Keywords

    carbon modeling, remote sensing, modeling, forest inventory, random forest

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