@InProceedings{MohanSKCACJH:2019:FoPlFi,
author = "Mohan, Midhun and Silva, Carlos Alberto and Klauberg, Carine and
Cardil, Adri{\'a}n and Almeida, Danilo and Carvalho, Samuel de
P{\'a}dua Chaves and Jaafar, Wan Shafrina Wan Mohd and Hudak,
Andrew T.",
affiliation = "{North Carolina State University} and {NASA Goddard Space Flight
Center} and {Universidade Federal de S{\~a}o Jo{\~a}o Del-Rei
(UFSJ)} and {Tecnosylva. Parque Tecnol{\'o}gico de Le{\'o}n} and
{Universidade de S{\~a}o Paulo (USP)} and {Universidade Federal
de Mato Grosso (UFMT)} and {University of Edinburgh} and {USDA
Forest Service}",
title = "Applying mixed-effects model for estimating individual tree
attributes in Eucalyptus spp. forest plantations from field and
airborne LiDAR data",
booktitle = "Anais...",
year = "2019",
editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco
and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
pages = "1055--1059",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "plantation forestry, forest productivity, above ground carbon
estimation, tree level attributes.",
abstract = "Forest plantations cover a large part of tropical countries such
as Brazil and eucalyptus plantations in particular account for 57%
of Brazils reforested area. As plantations offer multiple benefits
such as an option to offset natural forests, simplify otherwise
complex forest ecosystems, meet energy, pulp and paper demands,
restore ecological services and combat climate change by
sequestering carbon to the society, monitoring and tracking the
growth and productivity of forest plantations should be given high
priority. In this regard, remote sensing techniques have been
found highly efficient. The core objective of this study is to
estimate individual tree attributes, such as tree height, diameter
at breast height (dbh) and above ground carbon (AGC) stocks of
eucalyptus plantations from lidar data using linear mixed effects
(LME) models; Ordinary Least Square (OLS) regression models are
also built for comparison purposes. From our results, it can be
inferred that hierarchy existing within the plantation datasets
can be well handled by LME models and predictive models, for
tracking tree level AGC and forest productivity, with satisfactory
accuracies possible by combining lidar and LME modeling
techniques.",
conference-location = "Santos",
conference-year = "14-17 abril 2019",
isbn = "978-85-17-00097-3",
language = "pt",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/3U3RP7H",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U3RP7H",
targetfile = "97585.pdf",
type = "LIDAR: sensores e aplica{\c{c}}{\~o}es",
urlaccessdate = "18 jun. 2024"
}