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| 20. |  | MIRANDA, E. M. de; VALENTIM, J. F.; OLIVEIRA, M. V. N. d'. Avaliacao e selecao de especies arboreas nativas e introduzidas com potencial de uso multiplo em sistemas agroflorestais no Acre. In: CONGRESSO BRASILEIRO SOBRE SISTEMAS AGROFLORESTAIS, 1.; ENCONTRO SOBRE SISTEMAS AGROFLORESTAIS NOS PAÍSES DO MERCOSUL, 1., 1994, Porto Velho. Anais. Colombo: EMBRAPA-CNPF, 1994. v. 2, p. 209-218. (EMBRAPA-CNPF. documentos, 27).| Biblioteca(s): Embrapa Florestas. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Florestas. Para informações adicionais entre em contato com cnpf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
27/10/2016 |
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Data da última atualização: |
27/10/2016 |
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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: |
FIGUEIREDO, E. O.; OLIVEIRA, M. V. N. d'; BRAZ, E. M.; PAPA, D. de A.; FEARNSIDE, P. M. |
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Afiliação: |
EVANDRO ORFANO FIGUEIREDO, CPAF-Acre; MARCUS VINICIO NEVES D OLIVEIRA, CPAF-Acre; EVALDO MUNOZ BRAZ, CNPF; DANIEL DE ALMEIDA PAPA, CPAF-Acre; Philip Martin Fearnside, Instituto Nacional de Pesquisas da Amazônia/RedeClima. |
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Título: |
LIDAR-based estimation of bole biomass for precision management of an Amazonian forest: comparisons of ground-based and remotely sensed estimates. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Remote Sensing of Environment, Amsterdam, v. 187, p. 281-293, Dec. 2016. |
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Idioma: |
Inglês |
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Conteúdo: |
Based on airborne LIDAR data on canopymorphology and height ofAmazon forest trees, we developed allometric models to estimate dry biomass stored in the boles of dominant and co-dominant individuals and compared these results with those from equations based on traditional variables such as diameter at breast height (DBH). The database consisted of 142 trees of interest for logging in a forest under management for timber in Brazil's state of Acre. The trees chosen for studywere selected through proportional sampling by diameter class (ranging
from45 to 165 cm DBH) in order to properly represent the dominant and co-dominant tree populationswith diameters appropriate for harvest. Subsequent to LIDAR profiling of these trees, they were felled, subjected to a battery of dimensional measurements and sampled for wood-density determination. A set ofmodels was generated, followed by model selection and identity testing in order to compare groups of basicwood density (low, medium and high). The morphometric variables of the crown had high explanatory power for bole biomass independent of whether the allometric equations included DBH. When calculating bole biomass with equations that include basic wood density, the best estimate is obtained using variables for both DBH and crown morphology. To obtain an allometric equation that encompasses species in all three classes of basic density, one should either use only independent variables representing crown dimensions or complement these with variables for basic density (BD) and total height (Ht). The study demonstrates the feasibility of using ground-based measurements to calibrate biomass models that include only LIDAR-based variables, allowing much larger areas to be surveyed with reasonable accuracy. The present study is designed to produce data needed for forest management, but the
methods developed here can be adapted to studies aimed at reducing the uncertainty in biomass estimates of whole forests (not just harvestable trees) for use in quantifying carbon emissions from forest loss and degradation. MenosBased on airborne LIDAR data on canopymorphology and height ofAmazon forest trees, we developed allometric models to estimate dry biomass stored in the boles of dominant and co-dominant individuals and compared these results with those from equations based on traditional variables such as diameter at breast height (DBH). The database consisted of 142 trees of interest for logging in a forest under management for timber in Brazil's state of Acre. The trees chosen for studywere selected through proportional sampling by diameter class (ranging
from45 to 165 cm DBH) in order to properly represent the dominant and co-dominant tree populationswith diameters appropriate for harvest. Subsequent to LIDAR profiling of these trees, they were felled, subjected to a battery of dimensional measurements and sampled for wood-density determination. A set ofmodels was generated, followed by model selection and identity testing in order to compare groups of basicwood density (low, medium and high). The morphometric variables of the crown had high explanatory power for bole biomass independent of whether the allometric equations included DBH. When calculating bole biomass with equations that include basic wood density, the best estimate is obtained using variables for both DBH and crown morphology. To obtain an allometric equation that encompasses species in all three classes of basic density, one should either use only independent variables representing crown dimensions or complement these wit... Mostrar Tudo |
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Palavras-Chave: |
Biomassa seca; Biometria florestal; Manejo de precisão; Manejo florestal; Sistema de Informação Geográfica (SIG); Sistema de Posicionamento Geográfico (GPS). |
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Thesagro: |
Floresta Tropical. |
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Thesaurus NAL: |
Amazonia; lidar. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 03008naa a2200277 a 4500
001 2055467
005 2016-10-27
008 2016 bl --- 0-- u #d
100 1 $aFIGUEIREDO, E. O.
245 $aLIDAR-based estimation of bole biomass for precision management of an Amazonian forest$bcomparisons of ground-based and remotely sensed estimates.$h[electronic resource]
260 $c2016
520 $aBased on airborne LIDAR data on canopymorphology and height ofAmazon forest trees, we developed allometric models to estimate dry biomass stored in the boles of dominant and co-dominant individuals and compared these results with those from equations based on traditional variables such as diameter at breast height (DBH). The database consisted of 142 trees of interest for logging in a forest under management for timber in Brazil's state of Acre. The trees chosen for studywere selected through proportional sampling by diameter class (ranging from45 to 165 cm DBH) in order to properly represent the dominant and co-dominant tree populationswith diameters appropriate for harvest. Subsequent to LIDAR profiling of these trees, they were felled, subjected to a battery of dimensional measurements and sampled for wood-density determination. A set ofmodels was generated, followed by model selection and identity testing in order to compare groups of basicwood density (low, medium and high). The morphometric variables of the crown had high explanatory power for bole biomass independent of whether the allometric equations included DBH. When calculating bole biomass with equations that include basic wood density, the best estimate is obtained using variables for both DBH and crown morphology. To obtain an allometric equation that encompasses species in all three classes of basic density, one should either use only independent variables representing crown dimensions or complement these with variables for basic density (BD) and total height (Ht). The study demonstrates the feasibility of using ground-based measurements to calibrate biomass models that include only LIDAR-based variables, allowing much larger areas to be surveyed with reasonable accuracy. The present study is designed to produce data needed for forest management, but the methods developed here can be adapted to studies aimed at reducing the uncertainty in biomass estimates of whole forests (not just harvestable trees) for use in quantifying carbon emissions from forest loss and degradation.
650 $aAmazonia
650 $alidar
650 $aFloresta Tropical
653 $aBiomassa seca
653 $aBiometria florestal
653 $aManejo de precisão
653 $aManejo florestal
653 $aSistema de Informação Geográfica (SIG)
653 $aSistema de Posicionamento Geográfico (GPS)
700 1 $aOLIVEIRA, M. V. N. d'
700 1 $aBRAZ, E. M.
700 1 $aPAPA, D. de A.
700 1 $aFEARNSIDE, P. M.
773 $tRemote Sensing of Environment, Amsterdam$gv. 187, p. 281-293, Dec. 2016.
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