@InProceedings{DalagnolBSWSFOS:2023:QuCaLo,
author = "Dalagnol, Ricardo and Braga, Daniel and Silva J{\'u}nior, Celso
and Wagner, Fabien and Sagang, Le Bienfaiteur and Favrichon,
Samuel and Ometto, Jean Pierre Henry Balbaud and Saatchi, Sassan",
affiliation = "{University of California Los Angeles (UCLA)} and {Universidade
Federal de Juiz de Fora (UFJF)} and {University of California Los
Angeles (UCLA)} and {University of California Los Angeles (UCLA)}
and {University of California Los Angeles (UCLA)} and {NASA Jet
Propulsion Laboratory} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {NASA Jet Propulsion Laboratory}",
title = "Quantifying carbon loss at forests degraded by logging with
repeated airborne Lidar data in the Brazilian Amazon",
booktitle = "Anais...",
year = "2023",
editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
pages = "e155987",
organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 20. (SBSR)",
publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
address = "S{\~a}o Jos{\'e} dos Campos",
keywords = "forest degradation, LiDAR, carbon.",
abstract = "Forest degradation is a major issue and a key component of
tropical forests and carbon emissions. In this study, we use
repeated Airborne Laser Scanning (ALS) data to quantify carbon
losses in degraded forests due to logging at the Mato Grosso state
rainforests. We identified logged areas using Planet Norway's
International Climate and Forests Initiative (NICFI) satellite
imagery and estimated aboveground carbon density (ACD) and changes
(\ΔACD) using canopy structure derived from ALS data
acquired before and after the logging. Logging caused carbon
losses between 16-35% of the original ACD, but also as high as 89%
in heavily disturbed areas. Our findings bring estimates to
limited sites, so we recommend caution on using them for estimates
of carbon loss elsewhere. Spatialized and continuous estimates
should be explored in future studies connecting ALS estimates with
other optical and SAR remote sensing datasets.",
conference-location = "Florian{\'o}polis",
conference-year = "02-05 abril 2023",
isbn = "978-65-89159-04-9",
language = "en",
organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
ibi = "8JMKD3MGP6W34M/4944DHP",
url = "http://urlib.net/ibi/8JMKD3MGP6W34M/4944DHP",
targetfile = "155987.pdf",
type = "Degrada{\c{c}}{\~a}o de florestas",
urlaccessdate = "2024, May 02"
}