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 | Acesso ao texto completo restrito à biblioteca da Embrapa Acre. Para informações adicionais entre em contato com cpafac.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Acre. |
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Data corrente: |
27/07/2021 |
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Data da última atualização: |
19/11/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ALMEIDA, D. R. A. de; BROADBENT, E. N.; FERREIRA, M. P.; MELI, P.; ZAMBRANO, A. M. A.; GORGENS, E. B.; RESENDE, A. F.; ALMEIDA, C. T. de; AMARAL, C. R. do; CORTE, A. P. D.; SILVA, C. A.; ROMANELLI, J. P.; PRATA, G. A.; PAPA, D. de A.; STARK, S. C.; VALBUENA, R.; NELSON, B. W.; GUILLEMOT, J.; FÉRET, J. B.; CHAZDON, R.; BRANCALION, P. H. S. |
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Afiliação: |
DANILO ROBERTI ALVES DE ALMEIDA, "Luiz de Queiroz" College of Agriculture, University of São Paulo (USP/ESALQ) / University of Florida, Gainesville, FL, USA; EBEN NORTH BROADBENT, University of Florida, Gainesville, FL, USA; MATHEUS PINHEIRO FERREIRA, Military Institute of Engineering (IME); PAULA MELI, Universidad de La Frontera, Temuco, Chile; ANGELICA MARIA ALMEYDA ZAMBRANO, University of Florida, Gainesville, FL, USA; ERIC BASTOS GORGENS, Federal University of Jequitinhonha e Mucuri Valleys (UFVJM), Diamantina, Minas Gerais; ANGELICA FARIA RESENDE, "Luiz de Queiroz" College of Agriculture, University of São Paulo (USP/ESALQ); CATHERINE TORRES DE ALMEIDA, "Luiz de Queiroz" College of Agriculture, University of São Paulo (USP/ESALQ); CIBELE HUMMEL DO AMARAL, Federal University of Viçosa; ANA PAULA DALLA CORTE, Federal University of Parana; CARLOS ALBERTO SILVA, University of Florida / University of Maryland; JOÃO P. ROMANELLI, "Luiz de Queiroz" College of Agriculture, University of São Paulo (USP/ESALQ); GABRIEL ATTICCIATI PRATA, University of Florida, Gainesville, FL, USA; DANIEL DE ALMEIDA PAPA, CPAF-AC; SCOTT C. STARK, Michigan State University, East Lansing, MI, USA; RUBEN VALBUENA, Bangor University, Bangor, UK; BRUCE WALKER NELSON, National Institute for Amazon Research (INPA); JOANNES GUILLEMOT, "Luiz de Queiroz" College of Agriculture, University of Sao ˜ Paulo (USP/ESALQ) /; JEAN-BAPTISTE FÉRET, Université Montpellier, Montpellier, France; ROBIN CHAZDON, University of the Sunshine Coast, Australia; PEDRO H. S. BRANCALION, "Luiz de Queiroz" College of Agriculture, University of São Paulo (USP/ESALQ). |
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Título: |
Monitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Remote Sensing of Environment, v. 264, 112582, Oct. 2021. |
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ISSN: |
0034-4257 |
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DOI: |
https://doi.org/10.1016/j.rse.2021.112582 |
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Idioma: |
Inglês |
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Conteúdo: |
Remote sensors, onboard orbital platforms, aircraft, or unmanned aerial vehicles (UAVs) have emerged as a promising technology to enhance our understanding of changes in ecosystem composition, structure, and function of forests, offering multi-scale monitoring of forest restoration. UAV systems can generate highresolution images that provide accurate information on forest ecosystems to aid decision-making in restoration projects. However, UAV technological advances have outpaced practical application; thus, we explored combining UAV-borne lidar and hyperspectral data to evaluate the diversity and structure of restoration plantings. We developed novel analytical approaches to assess twelve 13-year-old restoration plots experimentally established with 20, 60 or 120 native tree species in the Brazilian Atlantic Forest. We assessed (1) the congruence and complementarity of lidar and hyperspectral-derived variables, (2) their ability to distinguish tree richness levels and (3) their ability to predict aboveground biomass (AGB). We analyzed three structural attributes derived from lidar data?canopy height, leaf area index (LAI), and understory LAI?and eighteen variables derived from hyperspectral data?15 vegetation indices (VIs), two components of the minimum noise fraction (related to spectral composition) and the spectral angle (related to spectral variability). We found that VIs were positively correlated with LAI for low LAI values, but stabilized for LAI greater than 2 m2/m2 . LAI and structural VIs increased with increasing species richness, and hyperspectral variability was significantly related to species richness. While lidar-derived canopy height better predicted AGB than hyperspectral-derived VIs, it was the fusion of UAV-borne hyperspectral and lidar data that allowed effective co-monitoring of both forest structural attributes and tree diversity in restoration plantings. Furthermore, considering lidar and hyperspectral data together more broadly supported the expectations of biodiversity theory, showing that diversity enhanced biomass capture and canopy functional attributes in restoration. The use of UAV-borne remote sensors can play an essential role during the UN Decade of Ecosystem Restoration, which requires detailed forest monitoring on an unprecedented scale. MenosRemote sensors, onboard orbital platforms, aircraft, or unmanned aerial vehicles (UAVs) have emerged as a promising technology to enhance our understanding of changes in ecosystem composition, structure, and function of forests, offering multi-scale monitoring of forest restoration. UAV systems can generate highresolution images that provide accurate information on forest ecosystems to aid decision-making in restoration projects. However, UAV technological advances have outpaced practical application; thus, we explored combining UAV-borne lidar and hyperspectral data to evaluate the diversity and structure of restoration plantings. We developed novel analytical approaches to assess twelve 13-year-old restoration plots experimentally established with 20, 60 or 120 native tree species in the Brazilian Atlantic Forest. We assessed (1) the congruence and complementarity of lidar and hyperspectral-derived variables, (2) their ability to distinguish tree richness levels and (3) their ability to predict aboveground biomass (AGB). We analyzed three structural attributes derived from lidar data?canopy height, leaf area index (LAI), and understory LAI?and eighteen variables derived from hyperspectral data?15 vegetation indices (VIs), two components of the minimum noise fraction (related to spectral composition) and the spectral angle (related to spectral variability). We found that VIs were positively correlated with LAI for low LAI values, but stabilized for LAI greater than 2 m2/m2 ... Mostrar Tudo |
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Palavras-Chave: |
Aeronave remotamente pilotada; Bosques tropicales; Drone; Hyperspectral remote sensing; Índice de vegetación; Leaf area density; Manejo florestal; Manejo forestal; Mata Atlântica; Monitoreo ambiental; Restauração florestal; Restauración de bosques; Vehículos aéreos no tripulados. |
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Thesagro: |
Área Foliar; Floresta Tropical; Raio Laser; Sensoriamento Remoto; Vegetação. |
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Thesaurus Nal: |
Environmental monitoring; Forest management; Forest restoration; Lidar; Tropical forests; Unmanned aerial vehicles; Vegetation index. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 04321naa a2200685 a 4500
001 2133117
005 2021-11-19
008 2021 bl uuuu u00u1 u #d
022 $a0034-4257
024 7 $ahttps://doi.org/10.1016/j.rse.2021.112582$2DOI
100 1 $aALMEIDA, D. R. A. de
245 $aMonitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion.$h[electronic resource]
260 $c2021
520 $aRemote sensors, onboard orbital platforms, aircraft, or unmanned aerial vehicles (UAVs) have emerged as a promising technology to enhance our understanding of changes in ecosystem composition, structure, and function of forests, offering multi-scale monitoring of forest restoration. UAV systems can generate highresolution images that provide accurate information on forest ecosystems to aid decision-making in restoration projects. However, UAV technological advances have outpaced practical application; thus, we explored combining UAV-borne lidar and hyperspectral data to evaluate the diversity and structure of restoration plantings. We developed novel analytical approaches to assess twelve 13-year-old restoration plots experimentally established with 20, 60 or 120 native tree species in the Brazilian Atlantic Forest. We assessed (1) the congruence and complementarity of lidar and hyperspectral-derived variables, (2) their ability to distinguish tree richness levels and (3) their ability to predict aboveground biomass (AGB). We analyzed three structural attributes derived from lidar data?canopy height, leaf area index (LAI), and understory LAI?and eighteen variables derived from hyperspectral data?15 vegetation indices (VIs), two components of the minimum noise fraction (related to spectral composition) and the spectral angle (related to spectral variability). We found that VIs were positively correlated with LAI for low LAI values, but stabilized for LAI greater than 2 m2/m2 . LAI and structural VIs increased with increasing species richness, and hyperspectral variability was significantly related to species richness. While lidar-derived canopy height better predicted AGB than hyperspectral-derived VIs, it was the fusion of UAV-borne hyperspectral and lidar data that allowed effective co-monitoring of both forest structural attributes and tree diversity in restoration plantings. Furthermore, considering lidar and hyperspectral data together more broadly supported the expectations of biodiversity theory, showing that diversity enhanced biomass capture and canopy functional attributes in restoration. The use of UAV-borne remote sensors can play an essential role during the UN Decade of Ecosystem Restoration, which requires detailed forest monitoring on an unprecedented scale.
650 $aEnvironmental monitoring
650 $aForest management
650 $aForest restoration
650 $aLidar
650 $aTropical forests
650 $aUnmanned aerial vehicles
650 $aVegetation index
650 $aÁrea Foliar
650 $aFloresta Tropical
650 $aRaio Laser
650 $aSensoriamento Remoto
650 $aVegetação
653 $aAeronave remotamente pilotada
653 $aBosques tropicales
653 $aDrone
653 $aHyperspectral remote sensing
653 $aÍndice de vegetación
653 $aLeaf area density
653 $aManejo florestal
653 $aManejo forestal
653 $aMata Atlântica
653 $aMonitoreo ambiental
653 $aRestauração florestal
653 $aRestauración de bosques
653 $aVehículos aéreos no tripulados
700 1 $aBROADBENT, E. N.
700 1 $aFERREIRA, M. P.
700 1 $aMELI, P.
700 1 $aZAMBRANO, A. M. A.
700 1 $aGORGENS, E. B.
700 1 $aRESENDE, A. F.
700 1 $aALMEIDA, C. T. de
700 1 $aAMARAL, C. R. do
700 1 $aCORTE, A. P. D.
700 1 $aSILVA, C. A.
700 1 $aROMANELLI, J. P.
700 1 $aPRATA, G. A.
700 1 $aPAPA, D. de A.
700 1 $aSTARK, S. C.
700 1 $aVALBUENA, R.
700 1 $aNELSON, B. W.
700 1 $aGUILLEMOT, J.
700 1 $aFÉRET, J. B.
700 1 $aCHAZDON, R.
700 1 $aBRANCALION, P. H. S.
773 $tRemote Sensing of Environment$gv. 264, 112582, Oct. 2021.
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Esconder MarcMostrar Marc Completo |
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Registro original: |
Embrapa Acre (CPAF-AC) |
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Biblioteca |
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Origem |
Tipo/Formato |
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| Registros recuperados : 15 | |
| 3. |  | PAPA, D. de A.; ALMEIDA, D. R. A. de; FIGUEIREDO, E. O.; OLIVEIRA, M. V. N. d'; CUNHA, R. M. da. Caracterização de floresta tropical primária com uso de Lidar. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 19., 2019, Santos, SP. Anais... São José dos Campos: INPE, 2019. 4 p.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Acre. |
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| 5. | | FERREIRA, M. P.; ALMEIDA, D. R. A. de; PAPA, D. de A.; MINERVINO, J. B. S.; VERAS, H. F. P.; FORMIGHIERI, A.; SANTOS, C. A. N.; FERREIRA, M. A. D.; FIGUEIREDO, E. O.; FERREIRA, E. J. L. Individual tree detection and species classification of Amazonian palms using UAV images and deep learning. Forest Ecology and Management, v. 475, n. 118397, p. 1-11, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Acre. |
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| 6. | | PAPA, D. de A.; ALMEIDA, D. R. A. de; SILVA, C. A.; FIGUEIREDO, E. O.; STARK, S. C.; VALBUENA, R.; RODRIGUEZ, L. C. E.; OLIVEIRA, M. V. N. d'. Evaluating tropical forest classification and field sampling stratification from lidar to reduce effort and enable landscape monitoring. Forest Ecology and Management, v. 457, 1176342019, Feb. 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Acre. |
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| 7. | | ROSENFIELD, M. F.; JAKOVAC, C. C.; VIEIRA, D. L. M.; POORTER, L.; BRANCALION, P. H, S.; VIEIRA, I. C. G.; ALMEIDA, D. R. A. de; MASSOCA, P.; SCHIETTI, J.; ALBERNAZ, A. L. M.; FERREIRA, M. J.; MESQUITA, R. C. G. Ecological integrity of tropical secondary forests: concepts and indicators. Biological Reviews; Cambridge Philosophical Society, v. 98, p. 662-676, 2023.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 8. | | OLIVEIRA, M. V. N. d'; FIGUEIREDO, E. O.; ALMEIDA, D. R. A. de; OLIVEIRA, L. C. de; SILVA, C. A.; NELSON, B. W.; CUNHA, R. M. da; PAPA, D. de A.; STARK, S. C.; VALBUENA, R. Impacts of selective logging on Amazon forest canopy structure and biomass with a LiDAR and photogrammetric survey sequence. Forest Ecology and Management, v. 500, 119648, Nov. 2021.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Acre. |
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| 9. | | 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.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Acre; Embrapa Instrumentação. |
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| 10. | | STARK, S. C.; BRESHEARS, D. D.; ARAGÓN, S.; VILLEGAS, J. C.; LAW, D. J.; SMITH, M. N.; MINOR, D. M.; ASSIS, R. L. de; ALMEIDA, D. R. A. de; OLIVEIRA, G. de; SALESKA, S. R.; SWANN, A. S.; MOURA, J. M. S.; CAMARGO, J. L.; SILVA, R. da; ARAGÃO, L. E. O. C.; OLIVEIRA JUNIOR, R. C. de. Reframing tropical savannization: linking changes in canopy structure to energy balance alterations that impact climate. Ecosphere, v. 11, n. 9, e03231, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 11. | | 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. Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar. Biotropica, v. 52, n. 6, p. 1155-1167, Nov. 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
| Biblioteca(s): Embrapa Acre. |
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| 12. | | ALMEIDA, D. R. A. de; BROADBENT, E. N.; FERREIRA, M. P.; MELI, P.; ZAMBRANO, A. M. A.; GORGENS, E. B.; RESENDE, A. F.; ALMEIDA, C. T. de; AMARAL, C. R. do; CORTE, A. P. D.; SILVA, C. A.; ROMANELLI, J. P.; PRATA, G. A.; PAPA, D. de A.; STARK, S. C.; VALBUENA, R.; NELSON, B. W.; GUILLEMOT, J.; FÉRET, J. B.; CHAZDON, R.; BRANCALION, P. H. S. Monitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion. Remote Sensing of Environment, v. 264, 112582, Oct. 2021.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Acre. |
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| 13. | | SMITH, M. N.; SCHITTI, J.; GONÇALVES, N.; MINOR, D.; ALMEIDA, D. R. A. de; ROCHA, D. G.; ARAGÓN, S.; MENIN, M.; GUEDES, M. C.; TONINI, H.; SILVA, K. E. da; ROSA, D. M.; NELSON, B. W.; CORDEIRO, C. L. O.; OLIVEIRA JUNIOR, R. C. de; SHAO, G.; SOUZA, M. S.; MCMAHON, S.; ALMEIDA, D.; ARAGÃO, L. E. O. C.; LIMA, N. Z. de; OLIVEIRA, G. de; ASSIS, R. L. de; CAMARGO, J. L.; MESQUITA, R. G.; SALESKA, S. R.; BRESHEARS, D. D.; COSTA, F. R. C.; STARK, S. C. Variations in Amazonian forest canopy structure and light environments across environmental and disturbance gradients. In: AGU FALL MEETING, 2019, San Francisco. Anais... San Francisco: AGU, 2019. Paper 499657.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Amapá; Embrapa Amazônia Ocidental; Embrapa Amazônia Oriental; Embrapa Pecuária Sul. |
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| 14. | | SMITH, M. N.; STARK, S. C.; TAYLOR, T. C.; SCHIETTI, J.; ALMEIDA, D. R. A. de; ARAGÓN, S.; TORRALVO, K.; LIMA, A. P.; OLIVEIRA, G. de; ASSIS, R. L. de; LEITOLD, V.; PONTES-LOPES, A.; SCOLES, R.; VIEIRA, L. C. de S.; RESENDE, A. F.; COPPOLA, A. I.; BRANDÃO, D. O.; SILVA JUNIOR, J. de A.; LOBATO, L. F.; FREITAS, W.; ALMEIDA, D.; SOUZA, M. S.; MINOR, D. M.; VILLEGAS, J. C.; LAW, D. J.; GONÇALVES, N.; ROCHA, D. G. da; GUEDES, M. C.; TONINI, H.; SILVA, K. E. da; HAREN, J. van; ROSA, D. M.; VALLE, D. F. do; CORDEIRO, C. L.; LIMA, N. Z. de; SHAO, G.; MENOR, I. O.; CONTI, G.; FLORENTINO, A. P.; MONTTI, L.; ARAGÃO, L. E. O. C.; McMAHON, S. M.; PARKER, G. G.; BRESHEARS, D. D.; COSTA, A. C. L. da; MAGNUSSON, W. E.; MESQUITA, R.; CAMARGO, J. L. C.; OLIVEIRA JUNIOR, R. C. de; CAMARGO, P. B. de; SALESKA, S. R.; NELSON, B. W. Diverse anthropogenic disturbances shift Amazon forests along a structural spectrum. Frontiers in Ecology an the Environment, v. 21, n. 1, p. 24-32, 2023.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Amapá; Embrapa Amazônia Ocidental; Embrapa Amazônia Oriental; Embrapa Pecuária Sul. |
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| 15. | | LIMA, R. B. de; GÖRGENS, E. B.; SILVA, D. A. S. da; OLIVEIRA, C. P. de; BATISTA, A. P. B.; FERREIRA, R. L. C.; COSTA, F. R. C.; LIMA, R. A. F. de; APARÍCIO, P. da S.; ABREU, J. C. de; SILVA, J. A. A. da; GUIMARAES, A. F.; FEARNSIDE, P. M.; SOUSA, T. R.; PERDIZ, R.; HIGUCHI, N.; BERENGUER, E.; RESENDE, A. F.; ELIAS, F.; CASTILHO, C. V. de; MEDEIROS, M. B. de; MATOS FILHO, J. R. de; SARDINHA, M. A.; FREITAS, M. A. F.; SILVA, J. J. da; CUNHA, A. P. da; SANTOS, R. M.; MUELBERT, A. E.; GUEDES, M. C.; IMBRÓZIO, R.; SOUSA, C. S. C. de; APARÍCIO, W. C. da S.; SILVA, B. M. da S. e; SILVA, C. A.; MARIMON, B. S.; MARIMON JUNIOR, B. H.; MORANDI, P. S.; STORCK-TONON, D.; VIEIRA, I. C. G.; SCHIETTI, J.; COELHO, F.; ALMEIDA, D. R. A. de; CASTRO, W.; CARVALHO, S. P. C.; SILVA, R. dos S. A. da; SILVEIRA, J.; CAMARGO, J. L.; MELGAÇO, K.; FREITAS, L. J. M. de; VEDOVATO, L.; BENCHIMOL, M.; ALMEIDA, G. de O. de; PRANCE, G.; SILVEIRA, A. B. da; SIMON, M. F.; GARCIA, M. L.; SILVEIRA, M.; VITAL, M.; ANDRADE, M. B. T.; SILVA, N.; ARAÚJO, R. O. de; CAVALHEIRO, L.; CARPANEDO, R.; FERNANDES, L.; MANZATTO, A. G.; ANDRADE, R. T. G. de; MAGNUSSON, W. E.; LAURANCE, B.; NELSON, B. W.; PERES, C.; DALY, D. C.; RODRIGUES, D.; ZOPELETTO, A. P.; OLIVEIRA, E. A. de; DUGACHARD, E.; BARBOSA, F. R.; SANTANA, F.; AMARAL, I. L. do; FERREIRA, L. V.; CHARÃO, L. S.; FERREIRA, J. N.; BARLOW, J.; BLANC, L.; ARAGÃO, L.; SIST, P.; SALOMÃO, R. de P.; SILVA, A. S. L. da; LAURANCE, S.; FELDPAUSCH, T. R.; GARDNER, T.; SANTIAGO, W.; BALEE, W.; LAURANCE, W. F.; MALHI, Y.; PHILLIPS, O. L. Giants of the Amazon: How does environmental variation drive the diversity patterns of large trees? Global Change Biology, 2023, v. 29, n. 17, p. 4861-4879, 2023. Na publicação: Joice Ferreira.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Amapá; Embrapa Amazônia Oriental; Embrapa Recursos Genéticos e Biotecnologia; Embrapa Roraima. |
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| Registros recuperados : 15 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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