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Registro Completo |
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
01/03/2011 |
Data da última atualização: |
07/12/2023 |
Tipo da produção científica: |
Comunicado Técnico/Recomendações Técnicas |
Autoria: |
NEVES, E. J. M.; SANTOS, A. F. dos; FRANCISCON, L. |
Afiliação: |
EDINELSON JOSE MACIEL NEVES, CNPF; ALVARO FIGUEREDO DOS SANTOS, CNPF; LUZIANE FRANCISCON, CNPF. |
Título: |
Métodos alternativos para o controle de ervas daninhas no cultivo da pupunheira para palmito no Estado de Santa Catarina. |
Ano de publicação: |
2010 |
Fonte/Imprenta: |
Colombo: Embrapa Florestas, 2010. |
Páginas: |
4 p. |
Série: |
(Embrapa Florestas. Comunicado técnico, 259). |
ISSN: |
1517-5030 |
Idioma: |
Português |
Palavras-Chave: |
Cultivo; Palmiteiro. |
Thesagro: |
Erva Daninha; Espécie nativa; Manejo; Palmito; Pupunha. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/28909/1/CT259.pdf
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Marc: |
LEADER 00700nam a2200241 a 4500 001 1879682 005 2023-12-07 008 2010 bl uuuu u0uu1 u #d 022 $a1517-5030 100 1 $aNEVES, E. J. M. 245 $aMétodos alternativos para o controle de ervas daninhas no cultivo da pupunheira para palmito no Estado de Santa Catarina. 260 $aColombo: Embrapa Florestas$c2010 300 $a4 p. 490 $a(Embrapa Florestas. Comunicado técnico, 259). 650 $aErva Daninha 650 $aEspécie nativa 650 $aManejo 650 $aPalmito 650 $aPupunha 653 $aCultivo 653 $aPalmiteiro 700 1 $aSANTOS, A. F. dos 700 1 $aFRANCISCON, L.
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Registro original: |
Embrapa Florestas (CNPF) |
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Biblioteca(s): |
Embrapa Territorial. |
Data corrente: |
02/03/2009 |
Data da última atualização: |
25/08/2014 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
Internacional - A |
Autoria: |
LU, D.; BATISTELLA, M.; MIRANDA, E. E. de. |
Afiliação: |
DENGSHENG LU, Indiana University; MATEUS BATISTELLA, CNPM; EVARISTO EDUARDO DE MIRANDA, CNPM. |
Título: |
A comparative study of landsat TM and SPOT HRG images of vegetation classification in the brazilian Amazon. |
Ano de publicação: |
2008 |
Fonte/Imprenta: |
Photogrammetric Engineering & Remote Sensing, v. 74, n. 3, p. 311-321, mar. 2008. |
Volume: |
v. 74 |
ISBN: |
0099-1112 |
Idioma: |
Inglês |
Conteúdo: |
Complex forest structure and abundant tree species in the moist tropical regions often couse difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HBG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG of TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels X 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. |
Palavras-Chave: |
Brazilian Amazon; Comparative study; Landsat TM and SPOT HRG Images; Machadinho d´Oeste; Moist tropical regions. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/107253/1/2284.pdf
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Marc: |
LEADER 02068naa a2200241 a 4500 001 1031577 005 2014-08-25 008 2008 bl uuuu u00u1 u #d 022 $a0099-1112 100 1 $aLU, D. 245 $aA comparative study of landsat TM and SPOT HRG images of vegetation classification in the brazilian Amazon. 260 $c2008 300 $av. 74 490 $vv. 74 520 $aComplex forest structure and abundant tree species in the moist tropical regions often couse difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HBG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG of TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels X 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. 653 $aBrazilian Amazon 653 $aComparative study 653 $aLandsat TM and SPOT HRG Images 653 $aMachadinho d´Oeste 653 $aMoist tropical regions 700 1 $aBATISTELLA, M. 700 1 $aMIRANDA, E. E. de 773 $tPhotogrammetric Engineering & Remote Sensing$gv. 74, n. 3, p. 311-321, mar. 2008.
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