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| 23. |  | LANZA, T. R.; MING, Lin Chau; HAVERROTH, M.; FERREIRA, A. B. Plantas alimentícias da Terra Indígena Kaxinawá de Nova Olinda, Acre, Brasil. Cadernos de Agroecologia, Porto Alegre, v. 13, n. 1, p. 1-7, Jul. 2018. Edição dos anais do VI Congresso Latino-Americano (CLAA), X Congresso Brasileiro (CBA), V Seminário do DF e Entorno (SEMDF), 12-15 setembro de 2017, Brasília, DF.| Biblioteca(s): Embrapa Acre. |
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| 25. | | ALVARES, V. de S.; LAMBERTUCCI, D. M.; SANTIAGO, A. C. C.; SENA, A. P. S. de; PEREIRA, A. M.; SOUZA, J. M. L. de. Rendimento da farinha de mandioca artesanal em função de diferentes concentrações de açafrão-da-terra. In: SEMINÁRIO DA EMBRAPA ACRE DE INICIAÇÃO CIENTÍFICA E PÓS-GRADUAÇÃO, 4., 2021, Rio Branco, AC. Atividades agropecuária e florestal para o desenvolvimento sustentável da Amazônia: anais. Rio Branco, AC: Embrapa Acre, 2022. Pôster. p. 111-116. (Embrapa Acre. Eventos técnicos & científicos, 4). Editores técnicos: Rodrigo Souza Santos; Fabiano Marçal Estanislau.| Biblioteca(s): Embrapa Acre. |
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| 31. | | OLIVEIRA, M. V. N. d'; BROADBENT, E. N.; OLIVEIRA, L. C. de; ALMEIDA, D. R. A.; PAPA, D. de A.; FERREIRA, M. E.; ZAMBRANO, A. M. A.; SILVA, C. A.; AVINO, F. S.; PRATA, G. A.; MELLO, R. A.; FIGUEIREDO, E. O.; JORGE, L. A. de C.; JUNIOR, L.; ALBUQUERQUE, R. W.; BRANCALION, P. H. S.; WILKINSON, B.; COSTA, M. O. da. Aboveground biomass estimation in Amazonian Tropical Forests: a comparison of aircraft- and GatorEye UAV- borne LiDAR data in the Chico Mendes Extractive Reserve in Acre, Brazil. Remote Sensing, v. 12, n. 11, 1754, May 2020.| Biblioteca(s): Embrapa Acre; Embrapa Instrumentação. |
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| 32. | | COSTA, F. de S.; DICK, D. P.; CAMPOS FILHO, M. D.; LAMBERTUCCI, D. M.; TAVELLA, L. B. Long-term no-fire conservation agriculture diversifies production on a sandy Acrisol in Acre state, southwestern Brazilian Amazon. In: WORLD CONGRESS ON CONSERVATION AGRICULTURE, 8., 2021, Bern, Switzerland. The Future of farming: profitable and sustainable farming with conservation agriculture: online proceedings. Brussels: ECAF, 2021. 1 p. Poster.| Biblioteca(s): Embrapa Acre. |
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| 34. | | LANZA, T. R.; MING, L. C.; HAVERROTH, M.; FERREIRA, A. B. Plantas alimentícias da Terra Indígena Kaxinawá de Nova Olinda, Acre, Brasil. Cadernos de Agroecologia, v. 13, n. 1, p. 1-7, Jul. 2018. Anais do VI Congresso Latino-americano de Agroecologia; X Congresso Brasileiro de Agroecologia; V Seminário de Agroecologia do Distrito Federal e Entorno; 12 a 15 de setembro de 2017, Brasília/DF.| Biblioteca(s): Embrapa Acre. |
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| 37. | | PIRES, S. A. de O.; MENDONÇA, A. R. de; SILVA, G. F. da; OLIVEIRA, M. V. N. d'; OLIVEIRA, L. C. de; SILVA, J. P. M.; SILVA, E. F. da. Growth modeling of Carapa guianensis and Tetragastris altissima for improved management in native forests in the Amazon. Ecological Modelling, v. 456, 109683, Sept. 2021.| Biblioteca(s): Embrapa Acre. |
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| 38. | | ANDRADE, C. M. S. de; GARCIA, R.; VALENTIM, J. F.; PEREIRA, O. G. Grazing management strategies for massaigrass-forage peanut pastures. 3. Definition of sward targets and carrying capacity. Revista Brasileira de Zootecnia, Viçosa, MG, v. 35, n. 2, p. 334-342, 2006.| Biblioteca(s): Embrapa Acre. |
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Registro Completo
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Biblioteca(s): |
Embrapa Acre; Embrapa Instrumentação. |
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Data corrente: |
01/06/2020 |
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Data da última atualização: |
28/06/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
OLIVEIRA, M. V. N. d'; BROADBENT, E. N.; OLIVEIRA, L. C. de; ALMEIDA, D. R. A.; PAPA, D. de A.; FERREIRA, M. E.; ZAMBRANO, A. M. A.; SILVA, C. A.; AVINO, F. S.; PRATA, G. A.; MELLO, R. A.; FIGUEIREDO, E. O.; JORGE, L. A. de C.; JUNIOR, L.; ALBUQUERQUE, R. W.; BRANCALION, P. H. S.; WILKINSON, B.; COSTA, M. O. da. |
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Afiliação: |
MARCUS VINICIO NEVES D OLIVEIRA, CPAF-AC; Eben N. Broadbent, University of Florida; LUIS CLAUDIO DE OLIVEIRA, CPAF-AC; Danilo R. A. Almeida, University of Florida / USP/ESALQ; DANIEL DE ALMEIDA PAPA, CPAF-AC; Manuel E. Ferreira, Universidade Federal de Goiás; Angelica M. Almeyda Zambrano, University of Florida; Carlos A. Silva, University of Florida / University of Maryland; Felipe S. Avino, WWF-Brasil; Gabriel A. Prata, University of Florida; Ricardo A. Mello, WWF-Brasil; EVANDRO ORFANO FIGUEIREDO, CPAF-AC; LUCIO ANDRE DE CASTRO JORGE, CNPDIA; Leomar Junior, Universidade Federal de Goiás; Rafael W. Albuquerque, Universidade de São Paulo; Pedro H. S. Brancalion, USP/ESALQ; Ben Wilkinson, University of Florida; Marcelo Oliveira-da-Costa, WWF-Brasil. |
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Título: |
Aboveground biomass estimation in Amazonian Tropical Forests: a comparison of aircraft- and GatorEye UAV- borne LiDAR data in the Chico Mendes Extractive Reserve in Acre, Brazil. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Remote Sensing, v. 12, n. 11, 1754, May 2020. |
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ISSN: |
2072-4292 |
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DOI: |
10.3390/rs12111754 |
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Idioma: |
Inglês |
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Conteúdo: |
Tropical forests are often located in dicult-to-access areas, which make high-quality forest structure information dicult and expensive to obtain by traditional field-based approaches.
LiDAR (acronym for Light Detection And Ranging) data have been used throughout the world to produce time-ecient and wall-to-wall structural parameter estimates for monitoring in native and commercial forests. In this study, we compare products and aboveground biomass (AGB) estimations from LiDAR data acquired using an aircraft-borne system in 2015 and data collected by the unmanned aerial vehicle (UAV)-based GatorEye Unmanned Flying Laboratory in 2017 for ten forest inventory plots located in the Chico Mendes Extractive Reserve in Acre state, southwestern Brazilian Amazon. The LiDAR products were similar and comparable among the two platforms and sensors. Principal dierences between derived products resulted from the GatorEye system flying lower and slower and having increased returns per second than the aircraft, resulting in a much higher point density overall (11.3 1.8 vs. 381.2 58 pts/m2). Dierences in ground point density, however, were much smaller among the systems, due to the larger pulse area and increased number of returns per pulse of the aircraft system, with the GatorEye showing an approximately 50% higher ground point density (0.27 0.09 vs. 0.42 0.09). The LiDAR models produced by both sensors presented similar results for digital elevation models and estimated AGB. Our results validate the ability for UAV-borne LiDAR sensors to accurately quantify AGB in dense high-leaf-area tropical forests in the Amazon. We also highlight new possibilities using the dense point clouds of UAV-borne systems for analyses of detailed crown structure and leaf area density distribution of the forest interior. MenosTropical forests are often located in dicult-to-access areas, which make high-quality forest structure information dicult and expensive to obtain by traditional field-based approaches.
LiDAR (acronym for Light Detection And Ranging) data have been used throughout the world to produce time-ecient and wall-to-wall structural parameter estimates for monitoring in native and commercial forests. In this study, we compare products and aboveground biomass (AGB) estimations from LiDAR data acquired using an aircraft-borne system in 2015 and data collected by the unmanned aerial vehicle (UAV)-based GatorEye Unmanned Flying Laboratory in 2017 for ten forest inventory plots located in the Chico Mendes Extractive Reserve in Acre state, southwestern Brazilian Amazon. The LiDAR products were similar and comparable among the two platforms and sensors. Principal dierences between derived products resulted from the GatorEye system flying lower and slower and having increased returns per second than the aircraft, resulting in a much higher point density overall (11.3 1.8 vs. 381.2 58 pts/m2). Dierences in ground point density, however, were much smaller among the systems, due to the larger pulse area and increased number of returns per pulse of the aircraft system, with the GatorEye showing an approximately 50% higher ground point density (0.27 0.09 vs. 0.42 0.09). The LiDAR models produced by both sensors presented similar results for digital elevation m... Mostrar Tudo |
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Palavras-Chave: |
Acre; Amazonia Occidental; Amazônia Ocidental; Biomassa aérea; Bosques tropicales; Drone; GatorEye; Inventario forestal; Monitoreo; RESEX Chico Mendes; Seringal Filipinas (AC); Teledetección; Vehículos aéreos no tripulados; Western Amazon. |
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Thesagro: |
Estimativa; Floresta Tropical; Inventário Florestal; Raio Laser; Reconhecimento Florestal; Sensoriamento Remoto. |
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Thesaurus NAL: |
Aboveground biomass; Forest inventory; Lidar; Monitoring; Remote sensing; Tropical forests; Unmanned aerial vehicles. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/213504/1/27002.pdf
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Marc: |
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022 $a2072-4292
024 7 $a10.3390/rs12111754$2DOI
100 1 $aOLIVEIRA, M. V. N. d'
245 $aAboveground biomass estimation in Amazonian Tropical Forests$ba comparison of aircraft- and GatorEye UAV- borne LiDAR data in the Chico Mendes Extractive Reserve in Acre, Brazil.$h[electronic resource]
260 $c2020
520 $aTropical forests are often located in dicult-to-access areas, which make high-quality forest structure information dicult and expensive to obtain by traditional field-based approaches. LiDAR (acronym for Light Detection And Ranging) data have been used throughout the world to produce time-ecient and wall-to-wall structural parameter estimates for monitoring in native and commercial forests. In this study, we compare products and aboveground biomass (AGB) estimations from LiDAR data acquired using an aircraft-borne system in 2015 and data collected by the unmanned aerial vehicle (UAV)-based GatorEye Unmanned Flying Laboratory in 2017 for ten forest inventory plots located in the Chico Mendes Extractive Reserve in Acre state, southwestern Brazilian Amazon. The LiDAR products were similar and comparable among the two platforms and sensors. Principal dierences between derived products resulted from the GatorEye system flying lower and slower and having increased returns per second than the aircraft, resulting in a much higher point density overall (11.3 1.8 vs. 381.2 58 pts/m2). Dierences in ground point density, however, were much smaller among the systems, due to the larger pulse area and increased number of returns per pulse of the aircraft system, with the GatorEye showing an approximately 50% higher ground point density (0.27 0.09 vs. 0.42 0.09). The LiDAR models produced by both sensors presented similar results for digital elevation models and estimated AGB. Our results validate the ability for UAV-borne LiDAR sensors to accurately quantify AGB in dense high-leaf-area tropical forests in the Amazon. We also highlight new possibilities using the dense point clouds of UAV-borne systems for analyses of detailed crown structure and leaf area density distribution of the forest interior.
650 $aAboveground biomass
650 $aForest inventory
650 $aLidar
650 $aMonitoring
650 $aRemote sensing
650 $aTropical forests
650 $aUnmanned aerial vehicles
650 $aEstimativa
650 $aFloresta Tropical
650 $aInventário Florestal
650 $aRaio Laser
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653 $aAcre
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653 $aMonitoreo
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653 $aSeringal Filipinas (AC)
653 $aTeledetección
653 $aVehículos aéreos no tripulados
653 $aWestern Amazon
700 1 $aBROADBENT, E. N.
700 1 $aOLIVEIRA, L. C. de
700 1 $aALMEIDA, D. R. A.
700 1 $aPAPA, D. de A.
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700 1 $aSILVA, C. A.
700 1 $aAVINO, F. S.
700 1 $aPRATA, G. A.
700 1 $aMELLO, R. A.
700 1 $aFIGUEIREDO, E. O.
700 1 $aJORGE, L. A. de C.
700 1 $aJUNIOR, L.
700 1 $aALBUQUERQUE, R. W.
700 1 $aBRANCALION, P. H. S.
700 1 $aWILKINSON, B.
700 1 $aCOSTA, M. O. da
773 $tRemote Sensing$gv. 12, n. 11, 1754, May 2020.
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Embrapa Acre (CPAF-AC) |
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