@InProceedings{AlmeidaGAOJPSSFL:2019:AbBiEs,
author = "Almeida, Catherine Torres de and Galv{\~a}o, L{\^e}nio Soares
and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de and Ometto, Jean
Pierre Henry Balbaud and Jacon, Aline Daniele and Pereira,
Francisca Rocha de Souza and Sato, Luciane Yumie and Silva, Camila
Val{\'e}ria de Jesus and Ferreira Ferreira, Jefferson and Longo,
Marcos",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and
{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Lancaster
University} and {Instituto de Desenvolvimento Sustent{\'a}vel
Mamirau{\'a}} and {Jet Propulsion Laboratory}",
title = "Aboveground biomass estimation in the brazilian Amazon using
combined LIDAR and hyperspectral 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 = "1843--1846",
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 = "imaging spectrometry, laser scanning, machine learning, biomass,
tropical forest.",
abstract = "Active Light Detection And Ranging (LiDAR) and passive
Hyperspectral Imaging (HSI) remote sensing provide complementary
information that can be combined to improve the estimation of
vegetation properties, such as aboveground biomass (AGB). Thus,
the main objective of this study is to evaluate the combined use
of LiDAR and HSI data for estimating AGB in the Brazilian Amazon,
by using six regression methods, a high range of remote sensing
metrics, and feature selection. To assess the prediction ability
of the remote sensing data, single and combined LiDAR and HSI
metrics were regressed against AGB from 147 sample plots across
the Brazilian Amazon Biome. Overall, the results showed a similar
model performance for both LiDAR and HSI single datasets, and for
the regression methods used. However, the combination of LiDAR and
HSI data improved the AGB estimation accuracy.",
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/3U255GH",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U255GH",
targetfile = "97359.pdf",
type = "Floresta e outros tipos de vegeta{\c{c}}{\~a}o",
urlaccessdate = "05 jun. 2024"
}