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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
05/05/2020 |
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Data da última atualização: |
06/05/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
AGUIAR, J. T. de; LOBO JUNIOR, M. |
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Afiliação: |
JORDENE TEIXEIRA DE AGUIAR, UFG; MURILLO LOBO JUNIOR, CNPAF. |
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Título: |
Reliability and discrepancies of rainfall and temperatures from remote sensing and Brazilian ground weather stations. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Remote Sensing Applications: Society and Environment, v. 18, 100301, Apr. 2020. |
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ISSN: |
2352-9385 |
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DOI: |
https://doi.org/10.1016/j.rsase.2020.100301 |
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Idioma: |
Inglês |
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Conteúdo: |
Insufficient ground meteorological stations limit agricultural research in wide geographic areas, but high-quality data from remote sensing may decrease information gaps, when surface stations are scarce. This study compared meteorological datasets, estimated from satellite and ground meteorological stations in latitudes from 0 to 33 oS, to support agricultural research in Brazil. The dataset comprised 3600 records of monthly temperatures and rainfall from 01 Jan 2004 to 31 Dec 2014 in 30 Brazilian municipalities distributed in six regions, labeled according to their precipitation homogeneity. Climatic records from NASA?s Prediction of Worldwide Energy Resource (POWER) online database were compared with data from Brazilian surface stations managed by National Institute of Meteorology (INMET). Monthly rainfall data showed satisfactory correlation coefficients for almost all locations, between 0.75 and 0.95 (p < 0.01), and simple linear models were fit for estimated (satellite) and observed (ground) rainfall relationship (p < 0.001). Complimentary accuracy and precision tests endorsed rainfall satellite-estimated data according to the root mean square error (RMSE) and the modified index of agreement. Maximum and minimum temperatures estimated by remote sensing in the Brazilian South Region were also statistically supported, but unsuitable results were found especially in lower latitudes, based on higher RMSE. The Pearson?s correlation coefficient for temperatures increased proportionally with latitude, while rainfall did not show this correlation. These results showed satellite-data quality varies regionally and is affected by seasonal variation. Remote sensors may not detect extreme climatic events such as heavy rainfall or draught and, therefore, need to be appraised carefully. MenosInsufficient ground meteorological stations limit agricultural research in wide geographic areas, but high-quality data from remote sensing may decrease information gaps, when surface stations are scarce. This study compared meteorological datasets, estimated from satellite and ground meteorological stations in latitudes from 0 to 33 oS, to support agricultural research in Brazil. The dataset comprised 3600 records of monthly temperatures and rainfall from 01 Jan 2004 to 31 Dec 2014 in 30 Brazilian municipalities distributed in six regions, labeled according to their precipitation homogeneity. Climatic records from NASA?s Prediction of Worldwide Energy Resource (POWER) online database were compared with data from Brazilian surface stations managed by National Institute of Meteorology (INMET). Monthly rainfall data showed satisfactory correlation coefficients for almost all locations, between 0.75 and 0.95 (p < 0.01), and simple linear models were fit for estimated (satellite) and observed (ground) rainfall relationship (p < 0.001). Complimentary accuracy and precision tests endorsed rainfall satellite-estimated data according to the root mean square error (RMSE) and the modified index of agreement. Maximum and minimum temperatures estimated by remote sensing in the Brazilian South Region were also statistically supported, but unsuitable results were found especially in lower latitudes, based on higher RMSE. The Pearson?s correlation coefficient for temperatures increased pro... Mostrar Tudo |
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Thesagro: |
Climatologia; Modelo de Simulação; Sensoriamento Remoto. |
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Thesaurus Nal: |
Agriculture; Climatology; Decision support systems; Remote sensing. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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001 2122081
005 2020-05-06
008 2020 bl uuuu u00u1 u #d
022 $a2352-9385
024 7 $ahttps://doi.org/10.1016/j.rsase.2020.100301$2DOI
100 1 $aAGUIAR, J. T. de
245 $aReliability and discrepancies of rainfall and temperatures from remote sensing and Brazilian ground weather stations.$h[electronic resource]
260 $c2020
520 $aInsufficient ground meteorological stations limit agricultural research in wide geographic areas, but high-quality data from remote sensing may decrease information gaps, when surface stations are scarce. This study compared meteorological datasets, estimated from satellite and ground meteorological stations in latitudes from 0 to 33 oS, to support agricultural research in Brazil. The dataset comprised 3600 records of monthly temperatures and rainfall from 01 Jan 2004 to 31 Dec 2014 in 30 Brazilian municipalities distributed in six regions, labeled according to their precipitation homogeneity. Climatic records from NASA?s Prediction of Worldwide Energy Resource (POWER) online database were compared with data from Brazilian surface stations managed by National Institute of Meteorology (INMET). Monthly rainfall data showed satisfactory correlation coefficients for almost all locations, between 0.75 and 0.95 (p < 0.01), and simple linear models were fit for estimated (satellite) and observed (ground) rainfall relationship (p < 0.001). Complimentary accuracy and precision tests endorsed rainfall satellite-estimated data according to the root mean square error (RMSE) and the modified index of agreement. Maximum and minimum temperatures estimated by remote sensing in the Brazilian South Region were also statistically supported, but unsuitable results were found especially in lower latitudes, based on higher RMSE. The Pearson?s correlation coefficient for temperatures increased proportionally with latitude, while rainfall did not show this correlation. These results showed satellite-data quality varies regionally and is affected by seasonal variation. Remote sensors may not detect extreme climatic events such as heavy rainfall or draught and, therefore, need to be appraised carefully.
650 $aAgriculture
650 $aClimatology
650 $aDecision support systems
650 $aRemote sensing
650 $aClimatologia
650 $aModelo de Simulação
650 $aSensoriamento Remoto
700 1 $aLOBO JUNIOR, M.
773 $tRemote Sensing Applications: Society and Environment$gv. 18, 100301, Apr. 2020.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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| Registros recuperados : 388 | |
| 3. |  | LOBO JUNIOR, M. Controle biológico do mofo branco. In: SIMPÓSIO DE CONTROLE BIOLÓGICO, 13., 2013, Bonito. Faça bonito: use controle biológico: anais. Brasília, DF: Embrapa, 2013. Siconbiol 2013.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 4. | | LOBO JUNIOR, M. Manejo integrado de doenças do feijoeiro comum. In: KLUTHCOUSKI, J.; STONE, L. F.; AIDAR, H. (Ed.). Fundamentos para uma agricultura sustentável, com ênfase na cultura do feijoeiro. Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2009. p. 309-328.| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 9. | | LOBO JUNIOR, M. Fungos no controle. Cultivar Grandes Culturas, v. 9, n. 95, p. 27-29, abr. 2007.| Tipo: Artigo em Periódico Indexado |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 18. | | LOBO JUNIOR, M. Manejo do mofo branco no Brasil Tropical Plant Pathology, Brasília, DF, v. 35, p. CI, ago. 2010. Suplemento. Edição dos resumos do XLIII Congresso Brasileiro de Fitopatologia, Cuiabá, ago. 2010. Grupo de discussãop 6: Controle de mofo branco.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 19. | | LOBO JUNIOR, M. Manejo do mofo branco. In: CONGRESSO NACIONAL DE PESQUISA DE FEIJÃO, 10., 2011, Goiânia. Anais... Goiânia: Embrapa Arroz e Feijão, 2011. 1 CD-ROM. Palestra - CONAFE.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| Registros recuperados : 388 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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