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| Registros recuperados : 7 | |
| 1. |  | SANCHES, I. D. A.; FEITOSA, R. Q.; DIAZ, P. M. A.; SOARES, M. D.; LUIZ, A. J. B.; SCHULTZ, B.; MAURANO, L. E. P. Campo Verde database: seeking to improve agricultural remote sensing of tropical areas. IEEE Geoscience and Remote Sensing Letters, v. 15, n. 3, p. 369-373, 2018.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 2. | | SANCHES, I. D.; FEITOSA, R. Q.; ACHANCCARAY, P.; MONTIBELLER, B.; LUIZ, A. J. B.; SOARES, M. D.; PRUDENTE, V. H. R.; VIEIRA, D. C.; MAURANO, L. E. P. Lem benchmark database for tropical agricultural remote sensing application. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. 42, n. 1, p. 387-392, 2018. Edition of the proceedings ISPRS TC I Mid-term Symposium ?Innovative Sensing ? From Sensors to Methods and Applications?, 10-12 October 2018, held a Karlsruhe, Germany. 387-392.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 3. | | SANCHES, I. D.; LUIZ, A. J. B.; MONTIBELLER, B.; SCHULTZ, B.; TRABAQUINI, K.; EBERHARDT, D. S.; FORMAGGIO, A. R.; MAURANO, L. E. P. Understanding the dynamic of tropical agriculture for remote sensing applications: a case study of Southeastern Brazil. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. 42, n. 3, p. 149-156, 2019. Edition of Proceedings of ISPRS-GEOGLAM-ISRS Joint Int. Workshop on Earth Observations for Agricultural Monitoring, 18-20 February 2019, New Delhi, India.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 4. | | SHIMABUKURO, Y. E.; DUARTE, V.; MOREIRA, M. A.; ARAI, E.; RUDORFF, B. F. T.; ANDERSON, L. O.; ESPIRITO SANTO, F. D. B.; FREITAS, R. M. de; AULICINO, L. C. M.; MAURANO, L. E. P.; ARAGÃO, J. R. L. de. Detecção de áreas desflorestadas em tempo real: conceitos básicos, desenvolvimento e aplicação do projeto deter. São José dos Campos: INPE, 2005. 1 CD-ROM. (INPE-12288-RPE/796).| Biblioteca(s): Embrapa Agropecuária Oeste. |
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| 5. | | ADAMI, M.; GOMES, A. R.; BELUZZO, A.; COELHO, A. dos S.; VALERIANO, D. de M.; RAMOS, F. de S.; NARVAES, I. da S.; BROWN, I. F.; OLIVEIRA, I. D. de; SANTOS, L. B.; MAURANO, L. E. P.; WATRIN, O. dos S.; GRAÇA, P. M. L. de A. A confiabilidade do PRODES: estimativa da acurácia do mapeamento do desmatamento no estado Mato Grosso. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... São José dos Campos: INPE, 2017. p. 4189-4196.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 6. | | SCARAMUZZA, C. A. de M.; SANO, E. E.; ADAMI, M.; BOLFE, E. L.; COUTINHO, A. C.; ESQUERDO, J. C. D. M.; MAURANO, L. E. P.; NARVAES, I. da S.; OLIVEIRA FILHO, F. J. B. de; ROSA, R.; SILVA, E. B. da; VALERIANO, D. de M.; VICTORIA, D. de C.; BAYMA, A. P.; OLIVEIRA, G. H. de; SILVA, G. B. S. da. Land-use and land-cover mapping of the Brazilian cerrado based mainly on Landsat-8 satellite images. Revista Brasileira de Cartografia, Rio de Janeiro, v. 69, n. 6, p. 1041-1051, jun. 2017. Título em português: Mapeamento de uso e cobertura de terras do cerrado com base principalmente em imagens do satélite Landsat-8.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Cerrados; Embrapa Territorial; Embrapa Unidades Centrais. |
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| 7. | | SANO, E. E.; ROSA, R.; SCARAMUZZA, C. A. de M.; ADAMI, M.; BOLFE, E. L.; COUTINHO, A. C.; ESQUERDO, J. C. D. M.; MAURANO, L. E. P.; NARVAES, I. da S.; OLIVEIRA FILHO, F. J. B. de; SILVA, E. B. da; VICTORIA, D. de C.; FERREIRA, L. G.; BRITO, J. L. S.; BAYMA, A. P.; OLIVEIRA, G. H. de O.; SILVA, G. B. S. da. Land use dynamics in the Brazilian Cerrado in the period from 2002 to 2013. Pesquisa Agropecuária Brasileira, v. 54, e00138, 2019. Título em português: Dinâmica do uso das terras no Cerrado no período de 2002 a 2013.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Cerrados; Embrapa Meio Ambiente; Embrapa Unidades Centrais. |
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| Registros recuperados : 7 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Meio Ambiente. Para informações adicionais entre em contato com cnpma.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
26/07/2018 |
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Data da última atualização: |
26/07/2018 |
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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: |
SANCHES, I. D. A.; FEITOSA, R. Q.; DIAZ, P. M. A.; SOARES, M. D.; LUIZ, A. J. B.; SCHULTZ, B.; MAURANO, L. E. P. |
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Afiliação: |
IARA DEL'ARCO SANCHES, INPE; RAUL QUEIROZ FEITOSA, PUC Rio; PEDRO MARCO ACHANCCARAY DIAZ, PUC Rio; MARINALVA DIAS SOARES, PUC Rio; ALFREDO JOSE BARRETO LUIZ, CNPMA; BRUNO SCHULTZ, Geoambiente; LUIS EDUARDO PINHEIRO MAURANO, INPE. |
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Título: |
Campo Verde database: seeking to improve agricultural remote sensing of tropical areas. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
IEEE Geoscience and Remote Sensing Letters, v. 15, n. 3, p. 369-373, 2018. |
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DOI: |
https://doi.org/10.1109/LGRS.2017.2789120 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: In tropical/subtropical regions, the favorable climate associated with the use of agricultural technologies, such as no tillage, minimum cultivation, irrigation, early varieties, desiccants, ?owering inducing, and crop rotation, makes agriculture highly dynamic. In this letter, we present the Campo Verde agricultural database. The purpose of creating and sharing these data is to foster advancement of remote sensing technology in areas of tropical agriculture, primarily the development and testingof methods for croprecognition andagriculturalmapping. Campo Verde is a municipality of Mato Grosso state, localized in the Cerrado (Brazilian Savanna) biome, in central west Brazil. Soybean, maize, and cotton are the primary crops cultivated in this region. Double cropping systems are widely adopted in this area. There is also livestock and forestry production. Our database provides the land-use classes for 513 ?elds by month for one Brazilian crop year (between October 2015 and July 2016). This information was gathered during two ?eld campaigns in Campo Verde (December 2015 and May 2016) and by visual interpretation of a time series of Landsat-8/Operational Land Imager (OLI) images using an experienced interpreter. A set of 14 preprocessed synthetic aperture radar Sentinel-1 and 15 Landsat-8/OLI mosaic images is also made available. It is important to promote the use of radar data for tropical agricultural applications, especially because the use of optical remote sensing in these regions is hindered by the high frequency of cloud cover. To demonstrate the utility of our database, results of an experiment conducted using the Sentinel-1 data set are presented. MenosAbstract: In tropical/subtropical regions, the favorable climate associated with the use of agricultural technologies, such as no tillage, minimum cultivation, irrigation, early varieties, desiccants, ?owering inducing, and crop rotation, makes agriculture highly dynamic. In this letter, we present the Campo Verde agricultural database. The purpose of creating and sharing these data is to foster advancement of remote sensing technology in areas of tropical agriculture, primarily the development and testingof methods for croprecognition andagriculturalmapping. Campo Verde is a municipality of Mato Grosso state, localized in the Cerrado (Brazilian Savanna) biome, in central west Brazil. Soybean, maize, and cotton are the primary crops cultivated in this region. Double cropping systems are widely adopted in this area. There is also livestock and forestry production. Our database provides the land-use classes for 513 ?elds by month for one Brazilian crop year (between October 2015 and July 2016). This information was gathered during two ?eld campaigns in Campo Verde (December 2015 and May 2016) and by visual interpretation of a time series of Landsat-8/Operational Land Imager (OLI) images using an experienced interpreter. A set of 14 preprocessed synthetic aperture radar Sentinel-1 and 15 Landsat-8/OLI mosaic images is also made available. It is important to promote the use of radar data for tropical agricultural applications, especially because the use of optical remote sensing... Mostrar Tudo |
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Palavras-Chave: |
Agricultural mapping/monitoring; Double cropping systems; Free available database. |
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Thesagro: |
Agricultura; Base de Dados; Sensoriamento Remoto. |
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Thesaurus NAL: |
Digital database; Monitoring; Remote sensing; Synthetic aperture radar; Tropical agriculture. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02742naa a2200337 a 4500
001 2093588
005 2018-07-26
008 2018 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1109/LGRS.2017.2789120$2DOI
100 1 $aSANCHES, I. D. A.
245 $aCampo Verde database$bseeking to improve agricultural remote sensing of tropical areas.$h[electronic resource]
260 $c2018
520 $aAbstract: In tropical/subtropical regions, the favorable climate associated with the use of agricultural technologies, such as no tillage, minimum cultivation, irrigation, early varieties, desiccants, ?owering inducing, and crop rotation, makes agriculture highly dynamic. In this letter, we present the Campo Verde agricultural database. The purpose of creating and sharing these data is to foster advancement of remote sensing technology in areas of tropical agriculture, primarily the development and testingof methods for croprecognition andagriculturalmapping. Campo Verde is a municipality of Mato Grosso state, localized in the Cerrado (Brazilian Savanna) biome, in central west Brazil. Soybean, maize, and cotton are the primary crops cultivated in this region. Double cropping systems are widely adopted in this area. There is also livestock and forestry production. Our database provides the land-use classes for 513 ?elds by month for one Brazilian crop year (between October 2015 and July 2016). This information was gathered during two ?eld campaigns in Campo Verde (December 2015 and May 2016) and by visual interpretation of a time series of Landsat-8/Operational Land Imager (OLI) images using an experienced interpreter. A set of 14 preprocessed synthetic aperture radar Sentinel-1 and 15 Landsat-8/OLI mosaic images is also made available. It is important to promote the use of radar data for tropical agricultural applications, especially because the use of optical remote sensing in these regions is hindered by the high frequency of cloud cover. To demonstrate the utility of our database, results of an experiment conducted using the Sentinel-1 data set are presented.
650 $aDigital database
650 $aMonitoring
650 $aRemote sensing
650 $aSynthetic aperture radar
650 $aTropical agriculture
650 $aAgricultura
650 $aBase de Dados
650 $aSensoriamento Remoto
653 $aAgricultural mapping/monitoring
653 $aDouble cropping systems
653 $aFree available database
700 1 $aFEITOSA, R. Q.
700 1 $aDIAZ, P. M. A.
700 1 $aSOARES, M. D.
700 1 $aLUIZ, A. J. B.
700 1 $aSCHULTZ, B.
700 1 $aMAURANO, L. E. P.
773 $tIEEE Geoscience and Remote Sensing Letters$gv. 15, n. 3, p. 369-373, 2018.
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