Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling

Detalhes bibliográficos
Autor(a) principal: Almeida, Danilo Roberti Alves de
Data de Publicação: 2019
Outros Autores: Stark, Scott C., Shao, Gang, Schietti, Juliana, Nelson, Bruce Walker, Silva, Carlos Alberto, Görgens, Eric Bastos, Valbuena, Rubén, Papa, Daniel de Almeida, Brancalion, Pedro Henrique Santin
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional do INPA
Texto Completo: https://repositorio.inpa.gov.br/handle/1/15584
Resumo: Airborne Laser Scanning (ALS) has been considered as a primary source to model the structure and function of a forest canopy through the indicators leaf area index (LAI) and vertical canopy profiles of leaf area density (LAD). However, little is known about the effects of the laser pulse density and the grain size (horizontal binning resolution) of the laser point cloud on the estimation of LAD profiles and their associated LAIs. Our objective was to determine the optimal values for reliable and stable estimates of LAD profiles from ALS data obtained over a dense tropical forest. Profiles were compared using three methods: Destructive field sampling, Portable Canopy profiling Lidar (PCL) and ALS. Stable LAD profiles from ALS, concordant with the other two analytical methods, were obtained when the grain size was less than 10 m and pulse density was high (> 15 pulses m -2 ). Lower pulse densities also provided stable and reliable LAD profiles when using an appropriate adjustment (coefficient K). We also discuss how LAD profiles might be corrected throughout the landscape when using ALS surveys of lower density, by calibrating with LAI measurements in the field or from PCL. Appropriate choices of grain size, pulse density and K provide reliable estimates of LAD and associated tree plot demography and biomass in dense forest ecosystems. © 2019 by the authors.
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spelling Almeida, Danilo Roberti Alves deStark, Scott C.Shao, GangSchietti, JulianaNelson, Bruce WalkerSilva, Carlos AlbertoGörgens, Eric BastosValbuena, RubénPapa, Daniel de AlmeidaBrancalion, Pedro Henrique Santin2020-05-15T00:09:41Z2020-05-15T00:09:41Z2019https://repositorio.inpa.gov.br/handle/1/1558410.3390/rs11010092Airborne Laser Scanning (ALS) has been considered as a primary source to model the structure and function of a forest canopy through the indicators leaf area index (LAI) and vertical canopy profiles of leaf area density (LAD). However, little is known about the effects of the laser pulse density and the grain size (horizontal binning resolution) of the laser point cloud on the estimation of LAD profiles and their associated LAIs. Our objective was to determine the optimal values for reliable and stable estimates of LAD profiles from ALS data obtained over a dense tropical forest. Profiles were compared using three methods: Destructive field sampling, Portable Canopy profiling Lidar (PCL) and ALS. Stable LAD profiles from ALS, concordant with the other two analytical methods, were obtained when the grain size was less than 10 m and pulse density was high (> 15 pulses m -2 ). Lower pulse densities also provided stable and reliable LAD profiles when using an appropriate adjustment (coefficient K). We also discuss how LAD profiles might be corrected throughout the landscape when using ALS surveys of lower density, by calibrating with LAI measurements in the field or from PCL. Appropriate choices of grain size, pulse density and K provide reliable estimates of LAD and associated tree plot demography and biomass in dense forest ecosystems. © 2019 by the authors.Volume 11, Número 1Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/info:eu-repo/semantics/openAccessEcosystemsGrain Size And ShapeOptical RadarTropicsAirborne Laser ScanningAnalytical MethodBeer Lambert LawCanopyLaser Pulse DensitiesLeaf Area IndexReliable EstimatesTropical Rain ForestForestryOptimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial samplinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleRemote Sensingengreponame:Repositório Institucional do INPAinstname:Instituto Nacional de Pesquisas da Amazônia (INPA)instacron:INPAORIGINALOptimizing.pdfOptimizing.pdfapplication/pdf5423607https://repositorio.inpa.gov.br/bitstream/1/15584/1/Optimizing.pdf9c0475966d80edec624236456e31fcd1MD511/155842020-05-28 15:53:50.69oai:repositorio:1/15584Repositório de PublicaçõesPUBhttps://repositorio.inpa.gov.br/oai/requestopendoar:2020-05-28T19:53:50Repositório Institucional do INPA - Instituto Nacional de Pesquisas da Amazônia (INPA)false
dc.title.en.fl_str_mv Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling
title Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling
spellingShingle Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling
Almeida, Danilo Roberti Alves de
Ecosystems
Grain Size And Shape
Optical Radar
Tropics
Airborne Laser Scanning
Analytical Method
Beer Lambert Law
Canopy
Laser Pulse Densities
Leaf Area Index
Reliable Estimates
Tropical Rain Forest
Forestry
title_short Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling
title_full Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling
title_fullStr Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling
title_full_unstemmed Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling
title_sort Optimizing the remote detection of tropical rainforest structure with airborne lidar: Leaf area profile sensitivity to pulse density and spatial sampling
author Almeida, Danilo Roberti Alves de
author_facet Almeida, Danilo Roberti Alves de
Stark, Scott C.
Shao, Gang
Schietti, Juliana
Nelson, Bruce Walker
Silva, Carlos Alberto
Görgens, Eric Bastos
Valbuena, Rubén
Papa, Daniel de Almeida
Brancalion, Pedro Henrique Santin
author_role author
author2 Stark, Scott C.
Shao, Gang
Schietti, Juliana
Nelson, Bruce Walker
Silva, Carlos Alberto
Görgens, Eric Bastos
Valbuena, Rubén
Papa, Daniel de Almeida
Brancalion, Pedro Henrique Santin
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Almeida, Danilo Roberti Alves de
Stark, Scott C.
Shao, Gang
Schietti, Juliana
Nelson, Bruce Walker
Silva, Carlos Alberto
Görgens, Eric Bastos
Valbuena, Rubén
Papa, Daniel de Almeida
Brancalion, Pedro Henrique Santin
dc.subject.eng.fl_str_mv Ecosystems
Grain Size And Shape
Optical Radar
Tropics
Airborne Laser Scanning
Analytical Method
Beer Lambert Law
Canopy
Laser Pulse Densities
Leaf Area Index
Reliable Estimates
Tropical Rain Forest
Forestry
topic Ecosystems
Grain Size And Shape
Optical Radar
Tropics
Airborne Laser Scanning
Analytical Method
Beer Lambert Law
Canopy
Laser Pulse Densities
Leaf Area Index
Reliable Estimates
Tropical Rain Forest
Forestry
description Airborne Laser Scanning (ALS) has been considered as a primary source to model the structure and function of a forest canopy through the indicators leaf area index (LAI) and vertical canopy profiles of leaf area density (LAD). However, little is known about the effects of the laser pulse density and the grain size (horizontal binning resolution) of the laser point cloud on the estimation of LAD profiles and their associated LAIs. Our objective was to determine the optimal values for reliable and stable estimates of LAD profiles from ALS data obtained over a dense tropical forest. Profiles were compared using three methods: Destructive field sampling, Portable Canopy profiling Lidar (PCL) and ALS. Stable LAD profiles from ALS, concordant with the other two analytical methods, were obtained when the grain size was less than 10 m and pulse density was high (> 15 pulses m -2 ). Lower pulse densities also provided stable and reliable LAD profiles when using an appropriate adjustment (coefficient K). We also discuss how LAD profiles might be corrected throughout the landscape when using ALS surveys of lower density, by calibrating with LAI measurements in the field or from PCL. Appropriate choices of grain size, pulse density and K provide reliable estimates of LAD and associated tree plot demography and biomass in dense forest ecosystems. © 2019 by the authors.
publishDate 2019
dc.date.issued.fl_str_mv 2019
dc.date.accessioned.fl_str_mv 2020-05-15T00:09:41Z
dc.date.available.fl_str_mv 2020-05-15T00:09:41Z
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/1/15584
dc.identifier.doi.none.fl_str_mv 10.3390/rs11010092
url https://repositorio.inpa.gov.br/handle/1/15584
identifier_str_mv 10.3390/rs11010092
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv Volume 11, Número 1
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
instname_str Instituto Nacional de Pesquisas da Amazônia (INPA)
instacron_str INPA
institution INPA
reponame_str Repositório Institucional do INPA
collection Repositório Institucional do INPA
bitstream.url.fl_str_mv https://repositorio.inpa.gov.br/bitstream/1/15584/1/Optimizing.pdf
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