Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
06/02/2017 |
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Data da última atualização: |
07/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
GRZEGOZEWSKI, D. M.; JOHANN, J. A.; URIBE-OPAZO, M. A.; MERCANTE, E.; COUTINHO, A. C. |
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Afiliação: |
DENISE MARIA GRZEGOZEWSKI, Unioeste; JERRY ADRIANI JOHANN, Unioeste; MIGUEL ANGEL URIBE-OPAZO, Unioeste; ERIVELTO MERCANTE, Unioeste; ALEXANDRE CAMARGO COUTINHO, CNPTIA. |
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Título: |
Mapping soya bean and corn crops in the State of Paraná, Brazil, using EVI images from the MODIS sensor. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
International Journal of Remote Sensing, Basingstoke, v. 37, n. 6, p. 1257-1275, 2016. |
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DOI: |
10.1080/01431161.2016.1148285 |
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Idioma: |
Inglês |
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Conteúdo: |
This study aimed to map, separate, and estimate soya bean and corn crop areas in Paraná State, Brazil, in the harvest years 2012/13 and 2013/14, using the enhanced vegetation index (EVI) images from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Thus, two methodologies were integrated, the first considering heterogeneity on the dates of crop cycles, the scenes required to generate images of minimum and maximum vegetation indexes, creating a colour composite red, green, and blue (RGB), and identifying two cultures simultaneously. In the second methodology, soya bean and corn were identified and mapped using the selection of pure pixels and the supervised classification algorithm Spectral Angle Mapper (SAM). In order to avoid overlapping areas, we multiplied the results from the first and second methodologies to obtain the final separation. The final validation of the mapping was compared to official data, identifying high correlation to crops. Based on Medium-Resolution Linear Imaging Self-Scanner (LISS-III) and Land Remote Sensing Satellite (Landsat-8) images, the similarity of global accuracy (GA) and kappa accuracy indices was determined, being classified as good and excellent, respectively. It showed that the use of the two consortium methodologies for separation and overlap elimination of these crops in the state of Paraná was efficient. |
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Palavras-Chave: |
Annual agriculture; Grãos de soja; Índice de vegetação; Soya bean. |
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Thesagro: |
Agricultura; Mapa; Milho; Soja. |
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Thesaurus NAL: |
Agriculture; Corn; Soybeans; Time series analysis; Vegetation index. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02372naa a2200337 a 4500
001 2062772
005 2020-01-07
008 2016 bl uuuu u00u1 u #d
024 7 $a10.1080/01431161.2016.1148285$2DOI
100 1 $aGRZEGOZEWSKI, D. M.
245 $aMapping soya bean and corn crops in the State of Paraná, Brazil, using EVI images from the MODIS sensor.$h[electronic resource]
260 $c2016
520 $aThis study aimed to map, separate, and estimate soya bean and corn crop areas in Paraná State, Brazil, in the harvest years 2012/13 and 2013/14, using the enhanced vegetation index (EVI) images from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Thus, two methodologies were integrated, the first considering heterogeneity on the dates of crop cycles, the scenes required to generate images of minimum and maximum vegetation indexes, creating a colour composite red, green, and blue (RGB), and identifying two cultures simultaneously. In the second methodology, soya bean and corn were identified and mapped using the selection of pure pixels and the supervised classification algorithm Spectral Angle Mapper (SAM). In order to avoid overlapping areas, we multiplied the results from the first and second methodologies to obtain the final separation. The final validation of the mapping was compared to official data, identifying high correlation to crops. Based on Medium-Resolution Linear Imaging Self-Scanner (LISS-III) and Land Remote Sensing Satellite (Landsat-8) images, the similarity of global accuracy (GA) and kappa accuracy indices was determined, being classified as good and excellent, respectively. It showed that the use of the two consortium methodologies for separation and overlap elimination of these crops in the state of Paraná was efficient.
650 $aAgriculture
650 $aCorn
650 $aSoybeans
650 $aTime series analysis
650 $aVegetation index
650 $aAgricultura
650 $aMapa
650 $aMilho
650 $aSoja
653 $aAnnual agriculture
653 $aGrãos de soja
653 $aÍndice de vegetação
653 $aSoya bean
700 1 $aJOHANN, J. A.
700 1 $aURIBE-OPAZO, M. A.
700 1 $aMERCANTE, E.
700 1 $aCOUTINHO, A. C.
773 $tInternational Journal of Remote Sensing, Basingstoke$gv. 37, n. 6, p. 1257-1275, 2016.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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