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| Registros recuperados : 9 | |
| 3. |  | LAURA, V. A.; RIZZON, M. H. DA S.; ALMEIDA, R. G. de; BUNGENSTAB, D. J.; OLIVEIRA, C. C. DE; PORFIRIO-DA-SILVA, V. Carbon sequestration by Eucalyptus urograndis (Clone H13) under integrated crop-livestock-forestry system. In: INTERNATIONAL SYMPOSIUM ON INTEGRATED CROP-LIVESTOCK SYSTEMS, 4., CONGRESSO BRASILEIRO DE SISTEMAS INTEGRADOS DE PRODUÇÃO AGROPECUÁRIA, 3., ENCONTRO DE SISTEMAS INTEGRADOS DE PRODUÇÃO AGROPECUÁRIA NO SUL DO BRASIL, 7., Bento Gonçalves, 2023. Anais... IV ICLS.| Biblioteca(s): Embrapa Florestas; Embrapa Gado de Corte. |
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| 4. | | COSTA, R. B. da; RESENDE, M. D. V. de; ROA, R. A. R.; BUNGENSTAB, D. J.; MARTINS, W. J.; ROEL, A. R. Melhoramento genético de erva-mate nativa do estado de Mato Grosso do Sul. Bragantia, Campinas, v. 68, n. 3, p. 611-619, 2009.| Biblioteca(s): Embrapa Florestas. |
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| 5. | | ALVES, F. V.; ALMEIDA, R. G. de; LAURA, V. A.; PORFIRIO-DA-SILVA, V.; MACEDO, M. C. M.; MEDEIROS, S. R. de; FERREIRA, A. D.; GOMES, R. da C.; BUNGENSTAB, D. J.; REIS, M. Carbon Neutral Brazilian Beef: a sustainable concept for beef production. In: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FOREST SYSTEMS; INTERNATIONAL SYMPOSIUM ON INTEGRATED CROP-LIVESTOCK SYSTEMS, 3., 2015, Brasília, DF. Towards sustainable intensification: proceedings. Brasília, DF: Embrapa, 2015. Resumo.| Biblioteca(s): Embrapa Florestas. |
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| 6. | | ALMEIDA, R. G. de; GOMES, R. da C.; PORFIRIO-DA-SILVA, V.; ALVES, F. V.; FEIJO, G. L. D.; FERREIRA, A. D.; OLIVEIRA, E. B. de; BUNGENSTAB, D. J. Carbon Neutral Brazilian Beef: testing its guidelines through a case study. In: INTERNATIONAL SYMPOSIUM ON GREENHOUSE GASES IN AGRICULTURE, 2., 2016, Campo Grande, MS. Proceedings... Brasília, DF: Embrapa, 2016. 502 p. (Embrapa Gado de Corte. Documentos, 216). Coordenador Roberto Giolo de Almeida. II SIGEE p. 277-281.| Biblioteca(s): Embrapa Florestas; Embrapa Gado de Corte. |
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| 7. | | ALMEIDA, R. G. de; GOMES, R. da C.; PORFIRIO-DA-SILVA, V.; ALVES, F. V.; FEIJO, G. L. D.; FERREIRA, A. D.; OLIVEIRA, E. B. de; BUNGENSTAB, D. J. Carne carbono neutro: testando as diretrizes em um estudo de caso. In: SOTTA, E. D.; SAMPAIO, F. G.; GUADALUPE GALLARDO, J. V. (org.). Coletânea dos fatores de emissão e remoção de gases de efeito estufa da agricultura brasileira. Brasília, DF: MAPA: SENAR, 2020. p. 63| Biblioteca(s): Embrapa Florestas; Embrapa Gado de Corte. |
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| 8. | | ALVES, F. V.; ALMEIDA, R. G. de; LAURA, V. A.; PORFIRIO-DA-SILVA, V.; GOMES, R. da C.; MACEDO, M. C. M.; PEREIRA, M. de A.; FERREIRA, A. D.; BUNGENSTAB, D. J. 50 perguntas, 50 respostas sobre a Carne Carbono Neutro (CCN). Brasília, DF: Embrapa, 2018 29 p. (Embrapa Gado de Corte. Documentos, 245).| Biblioteca(s): Embrapa Florestas; Embrapa Gado de Corte. |
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| 9. | | ZIMMER, A. H.; SALTON, J. C.; BALBINOT JUNIOR, A. A.; FRANCHINI, J. C.; PORFIRIO-DA-SILVA, V.; SANTAROSA, E.; BERNARDI, A. C. de C.; GARCIA, A. R.; BUNGENSTAB, D. J.; OMOTE, H. de S. G.; DEBIASI, H.; SOUZA FILHO, H. M. de; PEZZOPANE, J. R. M.; VINHOLIS, M. de M. B.; CARRER, M. J.; GUERREIRO, M. F. Sistemas ILPF e transferência de tecnologia nos estados do Mato Grosso do Sul, Paraná e São Paulo. In: SKORUPA, L. A.; MANZATTO, C. V. (Ed.). Sistemas de integração lavoura-pecuária-floresta no Brasil: estratégias regionais de transferência de tecnologia, avaliação da adoção e de impactos. Brasília: DF, Embrapa, 2019. p. 234-280| Biblioteca(s): Embrapa Agropecuária Oeste; Embrapa Florestas; Embrapa Gado de Corte; Embrapa Pecuária Sudeste. |
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| Registros recuperados : 9 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Pantanal. Para informações adicionais entre em contato com cpap.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Pantanal. |
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Data corrente: |
17/07/2014 |
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Data da última atualização: |
11/02/2015 |
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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: |
EVANS, T. L.; COSTA, M.; TOMAS, W. M.; CAMILO, A. R. |
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Afiliação: |
University of Victoria; University of Victoria; WALFRIDO MORAES TOMAS, CPAP. |
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Título: |
Large-scale habitat mapping of the Brazilian Pantanal wetland: A synthetic aperture radar approach. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Remote Sensing of Environment, v. 155, p. 89-108, 2014. |
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ISSN: |
0034-4257 |
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Idioma: |
Inglês |
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Conteúdo: |
This study uses 50 m spatial resolution, dual-season, HH and HV L-band ALOS/PALSAR, and HH and HV C-band RADARSAT-2 data, as well as a comprehensive set of ground reference points, to map the diverse habitats of the hydrologically variant subregions of the Pantanal by using a hierarchical object based image analysis approach. First, mean and standard deviation values of image object training sites were evaluated, and used as the basis for forming preliminary land cover class thresholds for each subregion. Then, acombination of additional refined thresholds, hierarchical rules, and a supervised nearest neighbor algorithm (eCognition Feature Space Optimization) employing several features as primary inputs (mean, standard deviation, seasonal change detection, brightness, maximum difference, area, roundness, brightness, compactness, shape index, and length/ width)wasutilized,resultinginthede finitionandclassificationoftenhabitatclasses:Forest/Woodland,Riparian Forest, Open Wood Savanna, Open Wood Savanna subject to prolonged flooding, Open Grass Savanna, Agriculture, Swampy Grassland, Swampy Mixed Savanna, Vazantes, and Water. This classification was achieved with an overall accuracy of 80% for the entire Pantanal. The produced habitat spatial distribution maps will provide vital information for determining refuge zones for terrestrial species, and connectivity of aquatic habitats during the dry season, as well as providing crucial baseline data to aid in monitoring changes in the region, and to help de fine conservation strategies for habitat in this wetland. MenosThis study uses 50 m spatial resolution, dual-season, HH and HV L-band ALOS/PALSAR, and HH and HV C-band RADARSAT-2 data, as well as a comprehensive set of ground reference points, to map the diverse habitats of the hydrologically variant subregions of the Pantanal by using a hierarchical object based image analysis approach. First, mean and standard deviation values of image object training sites were evaluated, and used as the basis for forming preliminary land cover class thresholds for each subregion. Then, acombination of additional refined thresholds, hierarchical rules, and a supervised nearest neighbor algorithm (eCognition Feature Space Optimization) employing several features as primary inputs (mean, standard deviation, seasonal change detection, brightness, maximum difference, area, roundness, brightness, compactness, shape index, and length/ width)wasutilized,resultinginthede finitionandclassificationoftenhabitatclasses:Forest/Woodland,Riparian Forest, Open Wood Savanna, Open Wood Savanna subject to prolonged flooding, Open Grass Savanna, Agriculture, Swampy Grassland, Swampy Mixed Savanna, Vazantes, and Water. This classification was achieved with an overall accuracy of 80% for the entire Pantanal. The produced habitat spatial distribution maps will provide vital information for determining refuge zones for terrestrial species, and connectivity of aquatic habitats during the dry season, as well as providing crucial baseline data to aid in monitoring changes in t... Mostrar Tudo |
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Palavras-Chave: |
ALOS/PALSAR; ENVISAT/ASAR; Habitat mapping; K&C Initiative; RADARSAT-2. |
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Thesaurus NAL: |
Pantanal; wetlands. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02267naa a2200253 a 4500
001 1990916
005 2015-02-11
008 2014 bl uuuu u00u1 u #d
022 $a0034-4257
100 1 $aEVANS, T. L.
245 $aLarge-scale habitat mapping of the Brazilian Pantanal wetland$bA synthetic aperture radar approach.
260 $c2014
520 $aThis study uses 50 m spatial resolution, dual-season, HH and HV L-band ALOS/PALSAR, and HH and HV C-band RADARSAT-2 data, as well as a comprehensive set of ground reference points, to map the diverse habitats of the hydrologically variant subregions of the Pantanal by using a hierarchical object based image analysis approach. First, mean and standard deviation values of image object training sites were evaluated, and used as the basis for forming preliminary land cover class thresholds for each subregion. Then, acombination of additional refined thresholds, hierarchical rules, and a supervised nearest neighbor algorithm (eCognition Feature Space Optimization) employing several features as primary inputs (mean, standard deviation, seasonal change detection, brightness, maximum difference, area, roundness, brightness, compactness, shape index, and length/ width)wasutilized,resultinginthede finitionandclassificationoftenhabitatclasses:Forest/Woodland,Riparian Forest, Open Wood Savanna, Open Wood Savanna subject to prolonged flooding, Open Grass Savanna, Agriculture, Swampy Grassland, Swampy Mixed Savanna, Vazantes, and Water. This classification was achieved with an overall accuracy of 80% for the entire Pantanal. The produced habitat spatial distribution maps will provide vital information for determining refuge zones for terrestrial species, and connectivity of aquatic habitats during the dry season, as well as providing crucial baseline data to aid in monitoring changes in the region, and to help de fine conservation strategies for habitat in this wetland.
650 $aPantanal
650 $awetlands
653 $aALOS/PALSAR
653 $aENVISAT/ASAR
653 $aHabitat mapping
653 $aK&C Initiative
653 $aRADARSAT-2
700 1 $aCOSTA, M.
700 1 $aTOMAS, W. M.
700 1 $aCAMILO, A. R.
773 $tRemote Sensing of Environment$gv. 155, p. 89-108, 2014.
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