Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional do INPA |
Texto Completo: | https://repositorio.inpa.gov.br/handle/1/15524 |
Resumo: | Tropical vegetation biomass represents a key component of the carbon stored in global forest ecosystems. Estimates of aboveground biomass commonly rely on measurements of tree size (diameter and height) and then indirectly relate, via allometric relationships and wood density, to biomass sampled from a relatively small number of harvested and weighed trees. Recently, however, novel in situ remote sensing techniques have been proposed, which may provide nondestructive alternative approaches to derive biomass estimates. Nonetheless, we still lack knowledge of the measurement uncertainties, as both the calibration and validation of estimates using different techniques and instruments requires consistent assessment of the underlying errors. To that end, we investigate different approaches estimating the tropical aboveground biomass in situ. We quantify the total and systematic errors among measurements obtained from terrestrial light detection and ranging (LiDAR), hypsometer-based trigonometry, and traditional forest inventory. We show that laser-based estimates of aboveground biomass are in good agreement (< 10% measurement uncertainty) with traditional measurements. However, relative uncertainties vary among the allometric equations based on the vegetation parameters used for parameterization. We report the error metrics for measurements of tree diameter and tree height and discuss the consequences for estimated biomass. Despite methodological differences detected in this study, we conclude that laser-based electronic devices could complement conventional measurement techniques, thereby potentially improving estimates of tropical vegetation biomass. © 2019 by the authors. |
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Pereira, Iokanam Salesdo Nascimento, Henrique E.MendonçaVicari, Matheus BoniDisney, Mathias I.DeLucia, Evan H.null, TomasKruijt, Bart J.Lapola, David MontenegroMeir, Patrick W.Norby, Richard J.Ometto, Jean Pierre Henry BalbaudQuesada, Carlos AlbertoRammig, AnjaHofhansl, Florian2020-05-14T16:32:39Z2020-05-14T16:32:39Z2019https://repositorio.inpa.gov.br/handle/1/1552410.3390/rs11050510Tropical vegetation biomass represents a key component of the carbon stored in global forest ecosystems. Estimates of aboveground biomass commonly rely on measurements of tree size (diameter and height) and then indirectly relate, via allometric relationships and wood density, to biomass sampled from a relatively small number of harvested and weighed trees. Recently, however, novel in situ remote sensing techniques have been proposed, which may provide nondestructive alternative approaches to derive biomass estimates. Nonetheless, we still lack knowledge of the measurement uncertainties, as both the calibration and validation of estimates using different techniques and instruments requires consistent assessment of the underlying errors. To that end, we investigate different approaches estimating the tropical aboveground biomass in situ. We quantify the total and systematic errors among measurements obtained from terrestrial light detection and ranging (LiDAR), hypsometer-based trigonometry, and traditional forest inventory. We show that laser-based estimates of aboveground biomass are in good agreement (< 10% measurement uncertainty) with traditional measurements. However, relative uncertainties vary among the allometric equations based on the vegetation parameters used for parameterization. We report the error metrics for measurements of tree diameter and tree height and discuss the consequences for estimated biomass. Despite methodological differences detected in this study, we conclude that laser-based electronic devices could complement conventional measurement techniques, thereby potentially improving estimates of tropical vegetation biomass. © 2019 by the authors.Volume 11, Número 5Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessBiomassEcosystemsElectronic EquipmentForestryInstrument ErrorsOptical RadarRemote SensingSystematic ErrorsThermoelectric EquipmentTropicsVegetationAmazoniaCarbon StorageForest StructureLight Detection And Ranging"terra Firme" ForestTerrestrial Laser ScanningUncertainty AnalysisPerformance of laser-based electronic devices for structural analysis of Amazonian terra-firme forestsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleRemote Sensingengreponame:Repositório Institucional do INPAinstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPAORIGINALartigo-inpa.pdfartigo-inpa.pdfapplication/pdf6491664https://repositorio.inpa.gov.br/bitstream/1/15524/1/artigo-inpa.pdf1026843adfe614c4c52a878f509e9934MD511/155242020-07-14 11:08:31.367oai:repositorio:1/15524Repositório de PublicaçõesPUBhttps://repositorio.inpa.gov.br/oai/requestopendoar:2020-07-14T15:08:31Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)false |
dc.title.en.fl_str_mv |
Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests |
title |
Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests |
spellingShingle |
Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests Pereira, Iokanam Sales Biomass Ecosystems Electronic Equipment Forestry Instrument Errors Optical Radar Remote Sensing Systematic Errors Thermoelectric Equipment Tropics Vegetation Amazonia Carbon Storage Forest Structure Light Detection And Ranging "terra Firme" Forest Terrestrial Laser Scanning Uncertainty Analysis |
title_short |
Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests |
title_full |
Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests |
title_fullStr |
Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests |
title_full_unstemmed |
Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests |
title_sort |
Performance of laser-based electronic devices for structural analysis of Amazonian terra-firme forests |
author |
Pereira, Iokanam Sales |
author_facet |
Pereira, Iokanam Sales do Nascimento, Henrique E.Mendonça Vicari, Matheus Boni Disney, Mathias I. DeLucia, Evan H. null, Tomas Kruijt, Bart J. Lapola, David Montenegro Meir, Patrick W. Norby, Richard J. Ometto, Jean Pierre Henry Balbaud Quesada, Carlos Alberto Rammig, Anja Hofhansl, Florian |
author_role |
author |
author2 |
do Nascimento, Henrique E.Mendonça Vicari, Matheus Boni Disney, Mathias I. DeLucia, Evan H. null, Tomas Kruijt, Bart J. Lapola, David Montenegro Meir, Patrick W. Norby, Richard J. Ometto, Jean Pierre Henry Balbaud Quesada, Carlos Alberto Rammig, Anja Hofhansl, Florian |
author2_role |
author author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Pereira, Iokanam Sales do Nascimento, Henrique E.Mendonça Vicari, Matheus Boni Disney, Mathias I. DeLucia, Evan H. null, Tomas Kruijt, Bart J. Lapola, David Montenegro Meir, Patrick W. Norby, Richard J. Ometto, Jean Pierre Henry Balbaud Quesada, Carlos Alberto Rammig, Anja Hofhansl, Florian |
dc.subject.eng.fl_str_mv |
Biomass Ecosystems Electronic Equipment Forestry Instrument Errors Optical Radar Remote Sensing Systematic Errors Thermoelectric Equipment Tropics Vegetation Amazonia Carbon Storage Forest Structure Light Detection And Ranging "terra Firme" Forest Terrestrial Laser Scanning Uncertainty Analysis |
topic |
Biomass Ecosystems Electronic Equipment Forestry Instrument Errors Optical Radar Remote Sensing Systematic Errors Thermoelectric Equipment Tropics Vegetation Amazonia Carbon Storage Forest Structure Light Detection And Ranging "terra Firme" Forest Terrestrial Laser Scanning Uncertainty Analysis |
description |
Tropical vegetation biomass represents a key component of the carbon stored in global forest ecosystems. Estimates of aboveground biomass commonly rely on measurements of tree size (diameter and height) and then indirectly relate, via allometric relationships and wood density, to biomass sampled from a relatively small number of harvested and weighed trees. Recently, however, novel in situ remote sensing techniques have been proposed, which may provide nondestructive alternative approaches to derive biomass estimates. Nonetheless, we still lack knowledge of the measurement uncertainties, as both the calibration and validation of estimates using different techniques and instruments requires consistent assessment of the underlying errors. To that end, we investigate different approaches estimating the tropical aboveground biomass in situ. We quantify the total and systematic errors among measurements obtained from terrestrial light detection and ranging (LiDAR), hypsometer-based trigonometry, and traditional forest inventory. We show that laser-based estimates of aboveground biomass are in good agreement (< 10% measurement uncertainty) with traditional measurements. However, relative uncertainties vary among the allometric equations based on the vegetation parameters used for parameterization. We report the error metrics for measurements of tree diameter and tree height and discuss the consequences for estimated biomass. Despite methodological differences detected in this study, we conclude that laser-based electronic devices could complement conventional measurement techniques, thereby potentially improving estimates of tropical vegetation biomass. © 2019 by the authors. |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019 |
dc.date.accessioned.fl_str_mv |
2020-05-14T16:32:39Z |
dc.date.available.fl_str_mv |
2020-05-14T16:32:39Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://repositorio.inpa.gov.br/handle/1/15524 |
dc.identifier.doi.none.fl_str_mv |
10.3390/rs11050510 |
url |
https://repositorio.inpa.gov.br/handle/1/15524 |
identifier_str_mv |
10.3390/rs11050510 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Volume 11, Número 5 |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivs 3.0 Brazil http://creativecommons.org/licenses/by-nc-nd/3.0/br/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Remote Sensing |
publisher.none.fl_str_mv |
Remote Sensing |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional do INPA instname:Instituto Nacional de Pesquisas da Amazônia (INPA) instacron:INPA |
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Instituto Nacional de Pesquisas da Amazônia (INPA) |
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INPA |
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INPA |
reponame_str |
Repositório Institucional do INPA |
collection |
Repositório Institucional do INPA |
bitstream.url.fl_str_mv |
https://repositorio.inpa.gov.br/bitstream/1/15524/1/artigo-inpa.pdf |
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1026843adfe614c4c52a878f509e9934 |
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Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA) |
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