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1. Identificação
Tipo de ReferênciaArtigo em Revista Científica (Journal Article)
Siteplutao.sid.inpe.br
Código do Detentorisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
IdentificadorJ8LNKAN8RW/36KNMEH
Repositóriodpi.inpe.br/plutao@80/2009/12.22.14.54.24
Última Atualização2010:09.15.13.47.32 (UTC) marciana
Repositório de Metadadosdpi.inpe.br/plutao@80/2009/12.22.14.54.25
Última Atualização dos Metadados2018:06.05.00.12.55 (UTC) administrator
Chave SecundáriaINPE--PRE/
DOI10.5194/bg-6-1883-2009
Rótulolattes: 7834780583735756 1 AndersonMLASPBCEHLLMNPQAV:2009:InLaHe
Chave de CitaçãoAndersonMLASPBCEHLLMNPQA:2009:InLaHe
TítuloInfluence of landscape heterogeneity on spatial patterns of wood productivity, wood specific density and above ground biomass in Amazonia
Ano2009
Data de Acesso13 maio 2024
Número de Arquivos1
Tamanho3676 KiB
2. Contextualização
Autor 1 Anderson, Liana Oighenstein
 2 Malhi, Yadvinder
 3 Ladle, Richard J.
 4 Aragão, Luiz Eduardo O. C.
 5 Shimabukuro, Yosio Edemir
 6 Phillips, Oliver
 7 Baker, Tim
 8 Costa, Antonio Lola da
 9 Espejo, Javier
10 Higuchi, Niro
11 Laurance, William F.
12 López-González, Gabi
13 Monteagudo, Abel
14 Núñez-Vargas, Percy
15 Peacock, July
16 Quesada, Carlos A.
17 Almeida, Samuel
Identificador de Curriculo 1
 2
 3
 4
 5 8JMKD3MGP5W/3C9JJCQ
Grupo 1
 2
 3
 4
 5 DSR-OBT-INPE-MCT-BR
Afiliação 1 Univ Oxford, Sch Geog & Environm, Oxford, England
 2 Univ Oxford, Sch Geog & Environm, Oxford, England
 3 Univ Oxford, Sch Geog & Environm, Oxford, England
 4 Univ Oxford, Sch Geog & Environm, Oxford, England
 5 Instituto Nacional de Pesquisas Espaciais (INPE)
 6 Univ Leeds, Sch Geog, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire England
 7 Univ Leeds, Sch Geog, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire England
 8 Fed Univ Para, BR-66059 Belem, Para Brazil
 9 Inst Natl Pesquisas Amazonia, Manaus, Amazonas Brazil
10 Inst Natl Pesquisas Amazonia, Manaus, Amazonas Brazil
11 Smithsonian Trop Res Inst, Balboa, Panama
12
13 Univ Nacl San Antonia Abad Cusco, Herbario Vargas, Cuzco, Peru
14 Univ Nacl San Antonia Abad Cusco, Herbario Vargas, Cuzco, Peru
15 Univ Leeds, Sch Geog, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire England
16 Univ Leeds, Sch Geog, Earth & Biosphere Inst, Leeds LS2 9JT, W Yorkshire England
17 Museu Paraense Emilio Goeldi, Belem, Para Brazil
Endereço de e-Mail do Autor 1 liana.anderson@ouce.ox.ac.uk
Endereço de e-Mailliana.anderson@ouce.ox.ac.uk
RevistaBiogeosciences
Volume6
Número9
Páginas1883-1902
Histórico (UTC)2009-12-23 14:00:46 :: lattes -> marciana ::
2010-01-04 17:51:35 :: marciana -> administrator ::
2010-01-26 15:36:55 :: administrator -> marciana ::
2010-05-11 14:45:40 :: marciana -> administrator ::
2010-05-12 02:06:39 :: administrator -> marciana ::
2011-12-07 11:31:33 :: marciana -> administrator :: 2009
2016-06-04 01:08:39 :: administrator -> marciana :: 2009
2016-10-04 14:18:26 :: marciana -> administrator :: 2009
2018-06-05 00:12:55 :: administrator -> marciana :: 2009
3. Conteúdo e estrutura
É a matriz ou uma cópia?é a matriz
Estágio do Conteúdoconcluido
Transferível1
Tipo do ConteúdoExternal Contribution
Tipo de Versãopublisher
Palavras-Chave: aboveground biomass
carbon cycle
forestry production
geomorphology
Landsat thematic mapper
landscape structure
remote sensing
wood
Amazonia
Heliconia
ResumoLong-term studies using the RAINFOR network of forest plots have generated significant insights into the spatial and temporal dynamics of forest carbon cycling in Amazonia. In this work, we map and explore the landscape context of several major RAINFOR plot clusters using Landsat ETM+ satellite data. In particular, we explore how representative the plots are of their landscape context, and test whether bias in plot location within landscapes may be influencing the regional mean values obtained for important forest biophysical parameters. Specifically, we evaluate whether the regional variations in wood productivity, wood specific density and above ground biomass derived from the RAINFOR network could be driven by systematic and unintentional biases in plot location. Remote sensing data covering 45 field plots were aggregated to generate landscape maps to identify the specific physiognomy of the plots. In the Landsat ETM+ data, it was possible to spectrally differentiate three types of terra firme forest, three types of forests over Paleovarzea geomorphologycal formation, two types of bamboo-dominated forest, palm forest, Heliconia monodominant vegetation, swamp forest, disturbed forests and land use areas. Overall, the plots were generally representative of the forest physiognomies in the landscape in which they are located. Furthermore, the analysis supports the observed regional trends in those important forest parameters. This study demonstrates the utility of landscape scale analysis of forest physiognomies for validating and supporting the finds of plot based studies. Moreover, the more precise geolocation of many key RAINFOR plot clusters achieved during this research provides important contextual information for studies employing the RAINFOR database.
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URL dos dados zipadoshttp://urlib.net/zip/J8LNKAN8RW/36KNMEH
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Arquivo Alvobg-6-1883-2009.pdf
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5. Fontes relacionadas
Unidades Imediatamente Superiores8JMKD3MGPCW/3ER446E
URL (dados não confiáveis)http://www.cosis.net/members/journals/df/recent.php?j_id=8
Acervo Hospedeirodpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notas
NotasDOAJ Directory of Open Access Journals Free
Campos Vaziosalternatejournal archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination format isbn issn lineage mark mirrorrepository month nextedition orcid parameterlist parentrepositories previousedition previouslowerunit progress project rightsholder schedulinginformation secondarydate secondarymark secondarytype session shorttitle sponsor subject tertiarymark tertiarytype typeofwork
7. Controle da descrição
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