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| Registros recuperados : 382 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
29/03/2017 |
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Data da última atualização: |
29/03/2017 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
ALVES, H. M. R.; VOLPATO, M. M. L.; VIEIRA, T. G. C.; MACIEL, D. A.; GONÇALVES, T. G.; DANTAS, M. F. |
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Afiliação: |
HELENA MARIA RAMOS ALVES, SAPC; EPAMIG SUL; EPAMIG SUL; EPAMIG SUL; EPAMIG SUL; EPAMIG SUL. |
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Título: |
Characterization and spectral monitoring of coffee lands in Brazil. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
In: THE INTERNATIONAL SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING, 23., 2016, Prague, Czeach Republic. Proceedings... |
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Volume: |
4-B8 |
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Páginas: |
p. 801-803 |
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Idioma: |
Inglês |
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Conteúdo: |
In Brazil, coffee production has great economic and social importance. Despite this fact, there is still a shortage of information regarding its spatial distribution, crop management and environment. The aim of this study was to carry out spectral monitoring of coffee lands and to characterize their environments using geotechnologies. Coffee fields with contiguous areas over 0.01 km2 within a 488.5 km2 region in the south of Minas Gerais state were selected for the study. Spectral data from the sensors OLI/Landsat 8 and the Shuttle Radar Topography Mission from 2014 to 2015 were obtained, as well as information on production areas, surface temperature, vegetation indexes, altitude and slope, were gathered and analyzed. The results indicate that there is great variation in the NDVI and NDWI values, with means ranging from 0.21 to 0.91 (NDVI) and 0.108 to 0.543 (NDWI). The altitude ranged from 803 to 1150 m, and the surface temperature from 20.9°C to 27.6°C. The altitude and the surface temperature distribution patterns were correlated with the vegetation indexes. The slope classes were very homogeneous, predominantly with declivities between 8 to 20%, characterized as wavy relief. This study made possible the characterization and monitoring of coffee lands and its results may be instrumental in decision-making processes related to coffee management. |
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Palavras-Chave: |
Coffee. |
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Thesagro: |
Sensoriamento remoto. |
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Thesaurus NAL: |
Landsat; Remote sensing; Surface temperature. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/158264/1/Characterization-and-spectral-monitoring-of-coffee.pdf
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Marc: |
LEADER 02157nam a2200253 a 4500
001 2067802
005 2017-03-29
008 2016 bl uuuu u00u1 u #d
100 1 $aALVES, H. M. R.
245 $aCharacterization and spectral monitoring of coffee lands in Brazil.$h[electronic resource]
260 $aIn: THE INTERNATIONAL SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING, 23., 2016, Prague, Czeach Republic. Proceedings...$c2016
300 $ap. 801-803 4-B8
490 $v4-B8
520 $aIn Brazil, coffee production has great economic and social importance. Despite this fact, there is still a shortage of information regarding its spatial distribution, crop management and environment. The aim of this study was to carry out spectral monitoring of coffee lands and to characterize their environments using geotechnologies. Coffee fields with contiguous areas over 0.01 km2 within a 488.5 km2 region in the south of Minas Gerais state were selected for the study. Spectral data from the sensors OLI/Landsat 8 and the Shuttle Radar Topography Mission from 2014 to 2015 were obtained, as well as information on production areas, surface temperature, vegetation indexes, altitude and slope, were gathered and analyzed. The results indicate that there is great variation in the NDVI and NDWI values, with means ranging from 0.21 to 0.91 (NDVI) and 0.108 to 0.543 (NDWI). The altitude ranged from 803 to 1150 m, and the surface temperature from 20.9°C to 27.6°C. The altitude and the surface temperature distribution patterns were correlated with the vegetation indexes. The slope classes were very homogeneous, predominantly with declivities between 8 to 20%, characterized as wavy relief. This study made possible the characterization and monitoring of coffee lands and its results may be instrumental in decision-making processes related to coffee management.
650 $aLandsat
650 $aRemote sensing
650 $aSurface temperature
650 $aSensoriamento remoto
653 $aCoffee
700 1 $aVOLPATO, M. M. L.
700 1 $aVIEIRA, T. G. C.
700 1 $aMACIEL, D. A.
700 1 $aGONÇALVES, T. G.
700 1 $aDANTAS, M. F.
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Embrapa Café (CNPCa) |
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