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Registro Completo |
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
12/08/2014 |
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Data da última atualização: |
12/08/2014 |
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Autoria: |
SORJ, B. |
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Título: |
Estado e classes sociais na agricultura brasileira. |
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Edição: |
2. ed. ampl. |
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Ano de publicação: |
1986 |
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Fonte/Imprenta: |
Rio de Janeiro: Guanabara, 1986 |
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Páginas: |
162 p. |
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Série: |
(Agricultura e Sociedade). |
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ISBN: |
8524500395 |
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Idioma: |
Português |
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Conteúdo: |
Crise estrutural e reorganizacao agraria; O complexo agroindustrial; O novo padrao de desenvolvimento agricola: carater da intervencao estatal; As transformacoes e a estrutura de classes e a estrutura funciaria. |
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Palavras-Chave: |
Agricultural development; Agroindustria; Agroindustrial complex; Agroindustry; Complexo agroindustrial. |
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Thesagro: |
Desenvolvimento Agrícola. |
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Categoria do assunto: |
B Sociologia Rural |
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Marc: |
LEADER 00834nam a2200229 a 4500
001 1992366
005 2014-08-12
008 1986 bl uuuu 00u1 u #d
020 $a8524500395
100 1 $aSORJ, B.
245 $aEstado e classes sociais na agricultura brasileira.
250 $a2. ed. ampl.
260 $aRio de Janeiro: Guanabara$c1986
300 $a162 p.
490 $a(Agricultura e Sociedade).
520 $aCrise estrutural e reorganizacao agraria; O complexo agroindustrial; O novo padrao de desenvolvimento agricola: carater da intervencao estatal; As transformacoes e a estrutura de classes e a estrutura funciaria.
650 $aDesenvolvimento Agrícola
653 $aAgricultural development
653 $aAgroindustria
653 $aAgroindustrial complex
653 $aAgroindustry
653 $aComplexo agroindustrial
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Embrapa Gado de Leite (CNPGL) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Cerrados. Para informações adicionais entre em contato com cpac.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Cerrados. |
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Data corrente: |
16/04/2024 |
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Data da última atualização: |
16/04/2024 |
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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: |
BUSSINGUER, J. DE F.; BAPTISTA, G. M. DE M.; SANO, E. E.; LEAL, F. A. |
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Afiliação: |
JALES DE FREITAS BUSSINGUER, UNIVERSIDADE DE BRASÍLIA; GUSTAVO MACEDO DE MELLO BAPTISTA, UNIVERSIDADE DE BRASÍLIA; EDSON EYJI SANO, CPAC; FABRÍCIO ASSIS LEAL, UNIVERSIDADE FEDERAL DO ACRE. |
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Título: |
Understanding the Spatio-Temporal Behavior of Sentinel-1 SAR Vegetation Indices Over the Brazilian Savanna. |
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Ano de publicação: |
2024 |
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Fonte/Imprenta: |
IEEE Transactions on Geoscience and Remote Sensing, v. 62, 2024. |
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ISSN: |
1558-0644 |
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Idioma: |
Inglês |
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Conteúdo: |
The behavior of five synthetic aperture radar (SAR) vegetation indices, namely, the dual-pol radar vegetation index (DpRVI), radar vegetation index (RVI) dual-pol, polarimetric RVI (PRVI), dual-pol SAR vegetation index (DPSVI), and modified DPSVI (DPSVIm) was investigated. The indices were derived from Sentinel-1 data between 2017 and 2021 for three vegetation classes (Forest, Savanna, and Grassland) in the Brasilia National Park (BNP), Brazil. Temporal profile analysis showed that all indices followed a seasonal pattern directly linked with the rainfall regime in the study site. DpRVI and RVI were related to the rate of radar signal variation over the vegetation as a function of seasonality. PRVI, DPSVI, and DPSVIm were directly related to the classes’ biomass levels and its seasonal variations over time. Precipitation and seasonal vegetation structure changes were relevant drivers of the shift and spread of the indices’ spatial distributions over time. A phenomenon called the index equalization effect was observed mainly on rainy dates, shifting and spreading the classes’ distributions to the same value ranges and degrading its separability. From a populational perspective, all indices presented associative intersections between all vegetation classes, despite the influence of seasonality. From a local perspective, DpRVI and RVI had disjoint intersections; PRVI maintained the associative relationships; and DPSVI and DPSVIm provided almost a complete separation between Forest and Grassland in all seasons. In both perspectives, DPSVIm outperformed the other indices in separating the classes by presenting the less than 72.15% average overlaps between all populational distributions and the highest H0 rejection rates, above 97% over time. MenosThe behavior of five synthetic aperture radar (SAR) vegetation indices, namely, the dual-pol radar vegetation index (DpRVI), radar vegetation index (RVI) dual-pol, polarimetric RVI (PRVI), dual-pol SAR vegetation index (DPSVI), and modified DPSVI (DPSVIm) was investigated. The indices were derived from Sentinel-1 data between 2017 and 2021 for three vegetation classes (Forest, Savanna, and Grassland) in the Brasilia National Park (BNP), Brazil. Temporal profile analysis showed that all indices followed a seasonal pattern directly linked with the rainfall regime in the study site. DpRVI and RVI were related to the rate of radar signal variation over the vegetation as a function of seasonality. PRVI, DPSVI, and DPSVIm were directly related to the classes’ biomass levels and its seasonal variations over time. Precipitation and seasonal vegetation structure changes were relevant drivers of the shift and spread of the indices’ spatial distributions over time. A phenomenon called the index equalization effect was observed mainly on rainy dates, shifting and spreading the classes’ distributions to the same value ranges and degrading its separability. From a populational perspective, all indices presented associative intersections between all vegetation classes, despite the influence of seasonality. From a local perspective, DpRVI and RVI had disjoint intersections; PRVI maintained the associative relationships; and DPSVI and DPSVIm provided almost a complete separation between Fore... Mostrar Tudo |
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Palavras-Chave: |
Parque Nacional de Brasília; Radar de abertura sintética. |
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Thesagro: |
Radar; Vegetação. |
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Thesaurus NAL: |
Synthetic aperture radar; Vegetation. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02524naa a2200241 a 4500
001 2163648
005 2024-04-16
008 2024 bl uuuu u00u1 u #d
022 $a1558-0644
100 1 $aBUSSINGUER, J. DE F.
245 $aUnderstanding the Spatio-Temporal Behavior of Sentinel-1 SAR Vegetation Indices Over the Brazilian Savanna.$h[electronic resource]
260 $c2024
520 $aThe behavior of five synthetic aperture radar (SAR) vegetation indices, namely, the dual-pol radar vegetation index (DpRVI), radar vegetation index (RVI) dual-pol, polarimetric RVI (PRVI), dual-pol SAR vegetation index (DPSVI), and modified DPSVI (DPSVIm) was investigated. The indices were derived from Sentinel-1 data between 2017 and 2021 for three vegetation classes (Forest, Savanna, and Grassland) in the Brasilia National Park (BNP), Brazil. Temporal profile analysis showed that all indices followed a seasonal pattern directly linked with the rainfall regime in the study site. DpRVI and RVI were related to the rate of radar signal variation over the vegetation as a function of seasonality. PRVI, DPSVI, and DPSVIm were directly related to the classes’ biomass levels and its seasonal variations over time. Precipitation and seasonal vegetation structure changes were relevant drivers of the shift and spread of the indices’ spatial distributions over time. A phenomenon called the index equalization effect was observed mainly on rainy dates, shifting and spreading the classes’ distributions to the same value ranges and degrading its separability. From a populational perspective, all indices presented associative intersections between all vegetation classes, despite the influence of seasonality. From a local perspective, DpRVI and RVI had disjoint intersections; PRVI maintained the associative relationships; and DPSVI and DPSVIm provided almost a complete separation between Forest and Grassland in all seasons. In both perspectives, DPSVIm outperformed the other indices in separating the classes by presenting the less than 72.15% average overlaps between all populational distributions and the highest H0 rejection rates, above 97% over time.
650 $aSynthetic aperture radar
650 $aVegetation
650 $aRadar
650 $aVegetação
653 $aParque Nacional de Brasília
653 $aRadar de abertura sintética
700 1 $aBAPTISTA, G. M. DE M.
700 1 $aSANO, E. E.
700 1 $aLEAL, F. A.
773 $tIEEE Transactions on Geoscience and Remote Sensing$gv. 62, 2024.
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