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| 1. |  | BATISTA, L. A. R.; REGITANO NETO, A. Melhoramento genético de gramíneas forrageiras. In:SEMANA DO ESTUDANTE, 13.,1999, Sao Carlos,SP. Utilizacao de forrageiras para intensificacao da producao de carne e leite. Anais... Sao Carlos: Embrapa Pecuaria Sudeste, 1999. p.4-19. Editado por Rogério T. Barbosa, Armando A. Rodrigues, Eli Schifller, Luciano A. Correa, Sergio Esteves.| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| Registros recuperados : 7 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
26/08/2011 |
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Data da última atualização: |
11/11/2022 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
VALENCIA, L. I. O.; MEIRELLES, M. S. P.; MARTORANO, L. G. |
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Afiliação: |
LUIS IVÁN ORTIZ VALENCIA, UFRJ/IESC; MARGARETH SIMOES PENELLO MEIRELLES, EMBRAPA LABEX EUROPA / CIRAD / UERJ; LUCIETA GUERREIRO MARTORANO, CPATU. |
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Título: |
Avaliação do modelo de mudança do uso do solo CLUE-S na presença de dependência espacial. |
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Ano de publicação: |
2011 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE, 2011. |
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Idioma: |
Português |
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Conteúdo: |
Land use changes impacts global environmental changes worldwide. Land use and cover changes (LUCC) are complex dynamical processes. In general, LUCC depends on geographical, environmental, social, economical and political factors with effects in diverse temporal and spatial scales. Great efforts are being made to create LUCC models, both theoretically and computationality. An important step in LUCC models is to quantify local influence of driving forces over the probability of occurrence of a specific land use type. This probability is usually quantified by a Logistic Regression Model. This paper compares a Logistic approach with a Spatial Lag Regression Model (SLRM). Generally, both approaches select different driving forces but SLRM incorporates spatial neighborhood information which is ignored by a logistic regression. Based on a lineal trend scenario for land use demand, simulations for land use changes for Coxim micro basin, Mato Grosso do Sul, were generated using CLUE-S program under a logistic and spatial regression models for the period 2001-2011. Simulation results for both approaches revealed elevated concordance indexes, high global accuracy and Kappa index, with respect to land use for the reference year of 2004. Differences were observed for spatial distribution for land use simulations for year 2011. The spatial regression approach simulation for 2011 reached less discrepancy to the land use demand for that year. |
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Palavras-Chave: |
Modelo de regressão; Uso do solo. |
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Thesagro: |
Simulação. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/40610/1/AVALIACAO-DO-MODELO-MUDANCA-USO-SOLO-CLUE-S.pdf
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Marc: |
LEADER 02051nam a2200169 a 4500
001 1898949
005 2022-11-11
008 2011 bl uuuu u00u1 u #d
100 1 $aVALENCIA, L. I. O.
245 $aAvaliação do modelo de mudança do uso do solo CLUE-S na presença de dependência espacial.$h[electronic resource]
260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 15., 2011, Curitiba. Anais... São José dos Campos: INPE$c2011
520 $aLand use changes impacts global environmental changes worldwide. Land use and cover changes (LUCC) are complex dynamical processes. In general, LUCC depends on geographical, environmental, social, economical and political factors with effects in diverse temporal and spatial scales. Great efforts are being made to create LUCC models, both theoretically and computationality. An important step in LUCC models is to quantify local influence of driving forces over the probability of occurrence of a specific land use type. This probability is usually quantified by a Logistic Regression Model. This paper compares a Logistic approach with a Spatial Lag Regression Model (SLRM). Generally, both approaches select different driving forces but SLRM incorporates spatial neighborhood information which is ignored by a logistic regression. Based on a lineal trend scenario for land use demand, simulations for land use changes for Coxim micro basin, Mato Grosso do Sul, were generated using CLUE-S program under a logistic and spatial regression models for the period 2001-2011. Simulation results for both approaches revealed elevated concordance indexes, high global accuracy and Kappa index, with respect to land use for the reference year of 2004. Differences were observed for spatial distribution for land use simulations for year 2011. The spatial regression approach simulation for 2011 reached less discrepancy to the land use demand for that year.
650 $aSimulação
653 $aModelo de regressão
653 $aUso do solo
700 1 $aMEIRELLES, M. S. P.
700 1 $aMARTORANO, L. G.
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Registro original: |
Embrapa Amazônia Oriental (CPATU) |
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