Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.

Detalhes bibliográficos
Autor(a) principal: ALMEIDA, D. R. A. de
Data de Publicação: 2020
Outros Autores: ZAMBRANO, A. M. A., BROADBENT, E. N., WENDT, A. L., FOSTER, P., WILKINSON, B. E., SALK, C., PAPA, D. de A., STARK, S. C., VALBUENA, R., GORGENS, E. B., SILVA, C. A., BRANCALION, P. H. S., FAGAN, M., MELI, P., CHAZDON, R.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1124130
https://doi.org/10.1111/btp.12814
Resumo: Drone-based remote sensing is a promising new technology that combines the benefits of ground-based and satellite-derived forest monitoring by collecting fine-scale data over relatively large areas in a cost-effective manner. Here, we explore the potential of the GatorEye drone-lidar system to monitor tropical forest succession by canopy structural attributes including canopy height, spatial heterogeneity, gap fraction, leaf area density (LAD) vertical distribution, canopy Shannon index (an index of LAD), leaf area index (LAI), and understory LAI. We focus on these variables? relationship to aboveground biomass (AGB) stocks and species diversity. In the Caribbean lowlands of northeastern Costa Rica, we analyze nine tropical forests stands (seven secondgrowth and two old-growth). Stands were relatively homogenous in terms of canopy height and spatial heterogeneity, but not in their gap fraction. Neither species density nor tree community Shannon diversity index was significantly correlated with the canopy Shannon index. Canopy height, LAI, and AGB did not show a clear pattern as a function of forest age. However, gap fraction and spatial heterogeneity increased with forest age, whereas understory LAI decreased with forest age. Canopy height was strongly correlated with AGB. The heterogeneous mosaic created by successional forest patches across human-managed tropical landscapes can now be better characterized. Drone-lidar systems offer the opportunity to improve assessment of forest recovery and develop general mechanistic carbon sequestration models that can be rapidly deployed to specific sites, an essential step for monitoring progress within the UN Decade on Ecosystem Restoration.
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spelling Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.DroneGatorEyeAerial surveysRegeneração florestalBiomassa aéreaBosques lluviososMonitoreoRestauración de bosquesBosques secundariosBiomasa aéreaTeledetecciónVehículos aéreos no tripuladosSarapiquíHeredia ProvinceCaribbean lowlandsNortheastern Costa RicaFloresta TropicalReconhecimento FlorestalFloresta SecundariaSensoriamento RemotoRaio LaserRain forestsMonitoringForest restorationSecondary forestsAboveground biomassRemote sensingUnmanned aerial vehiclesLidarDrone-based remote sensing is a promising new technology that combines the benefits of ground-based and satellite-derived forest monitoring by collecting fine-scale data over relatively large areas in a cost-effective manner. Here, we explore the potential of the GatorEye drone-lidar system to monitor tropical forest succession by canopy structural attributes including canopy height, spatial heterogeneity, gap fraction, leaf area density (LAD) vertical distribution, canopy Shannon index (an index of LAD), leaf area index (LAI), and understory LAI. We focus on these variables? relationship to aboveground biomass (AGB) stocks and species diversity. In the Caribbean lowlands of northeastern Costa Rica, we analyze nine tropical forests stands (seven secondgrowth and two old-growth). Stands were relatively homogenous in terms of canopy height and spatial heterogeneity, but not in their gap fraction. Neither species density nor tree community Shannon diversity index was significantly correlated with the canopy Shannon index. Canopy height, LAI, and AGB did not show a clear pattern as a function of forest age. However, gap fraction and spatial heterogeneity increased with forest age, whereas understory LAI decreased with forest age. Canopy height was strongly correlated with AGB. The heterogeneous mosaic created by successional forest patches across human-managed tropical landscapes can now be better characterized. Drone-lidar systems offer the opportunity to improve assessment of forest recovery and develop general mechanistic carbon sequestration models that can be rapidly deployed to specific sites, an essential step for monitoring progress within the UN Decade on Ecosystem Restoration.Danilo Roberti Alves de Almeida, Universdade de São Paulo (USP/ESALQ) / University of Florida; Angelica Maria Almeyda Zambrano, University of Florida; Eben North Broadbent, University of Florida; Amanda L. Wendt, Organization for Tropical Studies / EARTH University; Paul Foster, Reserva Ecológica Bijagual / University of Michigan; Benjamin E. Wilkinson, University of Florida; Carl Salk, University of Agricultural Sciences; DANIEL DE ALMEIDA PAPA, CPAF-AC; Scott Christopher Stark, Michigan State University; Ruben Valbuena, Bangor University; Eric Bastos Gorgens, Universidade Federal do Vale do Jequitinhonha e Mucuri; Carlos Alberto Silva, University of Florida / University of Maryland; Pedro Henrique Santin Brancalion, Universidade de São Paulo (USP/ESALQ); Matthew Fagan, University of Maryland; Paula Meli, Universidade de São Paulo (USP/ESALQ) / Universidad de La Frontera; Robin Chazdon, University of Connecticut / University of the Sunshine Coast.ALMEIDA, D. R. A. deZAMBRANO, A. M. A.BROADBENT, E. N.WENDT, A. L.FOSTER, P.WILKINSON, B. E.SALK, C.PAPA, D. de A.STARK, S. C.VALBUENA, R.GORGENS, E. B.SILVA, C. A.BRANCALION, P. H. S.FAGAN, M.MELI, P.CHAZDON, R.2020-08-01T11:12:46Z2020-08-01T11:12:46Z2020-07-312020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleBiotropica, v. 52, n. 6, p. 1155-1167, Nov. 2020.1744-7429http://www.alice.cnptia.embrapa.br/alice/handle/doc/1124130https://doi.org/10.1111/btp.12814enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2020-08-01T11:12:53Zoai:www.alice.cnptia.embrapa.br:doc/1124130Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542020-08-01T11:12:53falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542020-08-01T11:12:53Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.
title Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.
spellingShingle Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.
ALMEIDA, D. R. A. de
Drone
GatorEye
Aerial surveys
Regeneração florestal
Biomassa aérea
Bosques lluviosos
Monitoreo
Restauración de bosques
Bosques secundarios
Biomasa aérea
Teledetección
Vehículos aéreos no tripulados
Sarapiquí
Heredia Province
Caribbean lowlands
Northeastern Costa Rica
Floresta Tropical
Reconhecimento Florestal
Floresta Secundaria
Sensoriamento Remoto
Raio Laser
Rain forests
Monitoring
Forest restoration
Secondary forests
Aboveground biomass
Remote sensing
Unmanned aerial vehicles
Lidar
title_short Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.
title_full Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.
title_fullStr Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.
title_full_unstemmed Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.
title_sort Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar.
author ALMEIDA, D. R. A. de
author_facet ALMEIDA, D. R. A. de
ZAMBRANO, A. M. A.
BROADBENT, E. N.
WENDT, A. L.
FOSTER, P.
WILKINSON, B. E.
SALK, C.
PAPA, D. de A.
STARK, S. C.
VALBUENA, R.
GORGENS, E. B.
SILVA, C. A.
BRANCALION, P. H. S.
FAGAN, M.
MELI, P.
CHAZDON, R.
author_role author
author2 ZAMBRANO, A. M. A.
BROADBENT, E. N.
WENDT, A. L.
FOSTER, P.
WILKINSON, B. E.
SALK, C.
PAPA, D. de A.
STARK, S. C.
VALBUENA, R.
GORGENS, E. B.
SILVA, C. A.
BRANCALION, P. H. S.
FAGAN, M.
MELI, P.
CHAZDON, R.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Danilo Roberti Alves de Almeida, Universdade de São Paulo (USP/ESALQ) / University of Florida; Angelica Maria Almeyda Zambrano, University of Florida; Eben North Broadbent, University of Florida; Amanda L. Wendt, Organization for Tropical Studies / EARTH University; Paul Foster, Reserva Ecológica Bijagual / University of Michigan; Benjamin E. Wilkinson, University of Florida; Carl Salk, University of Agricultural Sciences; DANIEL DE ALMEIDA PAPA, CPAF-AC; Scott Christopher Stark, Michigan State University; Ruben Valbuena, Bangor University; Eric Bastos Gorgens, Universidade Federal do Vale do Jequitinhonha e Mucuri; Carlos Alberto Silva, University of Florida / University of Maryland; Pedro Henrique Santin Brancalion, Universidade de São Paulo (USP/ESALQ); Matthew Fagan, University of Maryland; Paula Meli, Universidade de São Paulo (USP/ESALQ) / Universidad de La Frontera; Robin Chazdon, University of Connecticut / University of the Sunshine Coast.
dc.contributor.author.fl_str_mv ALMEIDA, D. R. A. de
ZAMBRANO, A. M. A.
BROADBENT, E. N.
WENDT, A. L.
FOSTER, P.
WILKINSON, B. E.
SALK, C.
PAPA, D. de A.
STARK, S. C.
VALBUENA, R.
GORGENS, E. B.
SILVA, C. A.
BRANCALION, P. H. S.
FAGAN, M.
MELI, P.
CHAZDON, R.
dc.subject.por.fl_str_mv Drone
GatorEye
Aerial surveys
Regeneração florestal
Biomassa aérea
Bosques lluviosos
Monitoreo
Restauración de bosques
Bosques secundarios
Biomasa aérea
Teledetección
Vehículos aéreos no tripulados
Sarapiquí
Heredia Province
Caribbean lowlands
Northeastern Costa Rica
Floresta Tropical
Reconhecimento Florestal
Floresta Secundaria
Sensoriamento Remoto
Raio Laser
Rain forests
Monitoring
Forest restoration
Secondary forests
Aboveground biomass
Remote sensing
Unmanned aerial vehicles
Lidar
topic Drone
GatorEye
Aerial surveys
Regeneração florestal
Biomassa aérea
Bosques lluviosos
Monitoreo
Restauración de bosques
Bosques secundarios
Biomasa aérea
Teledetección
Vehículos aéreos no tripulados
Sarapiquí
Heredia Province
Caribbean lowlands
Northeastern Costa Rica
Floresta Tropical
Reconhecimento Florestal
Floresta Secundaria
Sensoriamento Remoto
Raio Laser
Rain forests
Monitoring
Forest restoration
Secondary forests
Aboveground biomass
Remote sensing
Unmanned aerial vehicles
Lidar
description Drone-based remote sensing is a promising new technology that combines the benefits of ground-based and satellite-derived forest monitoring by collecting fine-scale data over relatively large areas in a cost-effective manner. Here, we explore the potential of the GatorEye drone-lidar system to monitor tropical forest succession by canopy structural attributes including canopy height, spatial heterogeneity, gap fraction, leaf area density (LAD) vertical distribution, canopy Shannon index (an index of LAD), leaf area index (LAI), and understory LAI. We focus on these variables? relationship to aboveground biomass (AGB) stocks and species diversity. In the Caribbean lowlands of northeastern Costa Rica, we analyze nine tropical forests stands (seven secondgrowth and two old-growth). Stands were relatively homogenous in terms of canopy height and spatial heterogeneity, but not in their gap fraction. Neither species density nor tree community Shannon diversity index was significantly correlated with the canopy Shannon index. Canopy height, LAI, and AGB did not show a clear pattern as a function of forest age. However, gap fraction and spatial heterogeneity increased with forest age, whereas understory LAI decreased with forest age. Canopy height was strongly correlated with AGB. The heterogeneous mosaic created by successional forest patches across human-managed tropical landscapes can now be better characterized. Drone-lidar systems offer the opportunity to improve assessment of forest recovery and develop general mechanistic carbon sequestration models that can be rapidly deployed to specific sites, an essential step for monitoring progress within the UN Decade on Ecosystem Restoration.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-01T11:12:46Z
2020-08-01T11:12:46Z
2020-07-31
2020
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Biotropica, v. 52, n. 6, p. 1155-1167, Nov. 2020.
1744-7429
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1124130
https://doi.org/10.1111/btp.12814
identifier_str_mv Biotropica, v. 52, n. 6, p. 1155-1167, Nov. 2020.
1744-7429
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1124130
https://doi.org/10.1111/btp.12814
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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