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

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

Abstract Background LiDAR remote sensing is a rapidly evolving technology for quantifying a variety of forest attributes, including aboveground carbon (AGC). Pulse density influences the acquisition cost of LiDAR, and grid cell size influences AGC prediction using plot-based methods; however, little...

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Bibliographic Details
Main Authors: Carlos Alberto Silva, Andrew Thomas Hudak, Carine Klauberg, Lee Alexandre Vierling, Carlos Gonzalez-Benecke, Samuel de Padua Chaves Carvalho, Luiz Carlos Estraviz Rodriguez, Adrián Cardil
Format: Article
Language:English
Published: BMC 2017-06-01
Series:Carbon Balance and Management
Subjects:
Carbon modeling
Remote sensing
Modeling
Forest inventory
Random forest
Online Access:http://link.springer.com/article/10.1186/s13021-017-0081-1

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