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| Registros recuperados : 186 | |
| 81. |  | MANJOLIN, R.; GREGO, C. R.; NOGUEIRA, S. F.; SILVA, G. B. S. da; TRABAQUINI, K.; SANCHES, I. D. Variabilidade espacial da fertilidade, carbono e nitrogênio do solo em áreas de pastagem e cana-de-açúcar no estado de São Paulo. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 18., 2017, Santos. Anais... Santos: Inpe, 2017. p. 7163-7170.| Biblioteca(s): Embrapa Territorial. |
|    |
| 82. | | TEIXEIRA, A. H. de C.; LEIVAS, J. F.; RONQUIM, C. C.; GARCON, E. A. M.; SILVA, G. B. S. da. Water and vegetation indices by using MODIS products for eucalyptus, pasture, and natural ecosystems in the eastern São Paulo state, Southeast Brazil. In: REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY, 19., 2017, Warsaw. Proceedings... Warsaw: SPIE, 2017. (SPIE proceedings, v. 10421). p. 1042112-1-1042112-12.| Biblioteca(s): Embrapa Territorial. |
|  |
| 83. | | LEIVAS, J. F.; TEIXEIRA, A. H. de C.; SILVA, G. B. S. da; GARCON, E. A. M.; RONQUIM, C. C. Water indicators based on SPOT 6 satellite images in irrigated area at the Paracatu River Basin, Brazil. In: REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY, 19., 2017, Warsaw. Proceedings... Warsaw: SPIE, 2017. (SPIE proceedings, v. 10421). p. 104211l-1-104211l-7.| Biblioteca(s): Embrapa Territorial. |
| |
| 84. | | TEIXEIRA, A. H. de C.; REIS, J. B. R. DA S.; LEIVAS, J. F.; SILVA, G. B. S. da; STRUIVING, T. B. Componentes da produtividade da água modelados por sensoriamento remoto em limoeiros irrigados de Minas Gerais. Agrometeoros, Passo Fundo, v. 25, n. 1, p. 237-247, ago. 2017.| Biblioteca(s): Embrapa Territorial. |
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| 85. | | SANO, E. E.; RIZZOLI, P.; KOYAMA, C. N.; WATANABE, M.; ADAMI, M.; SHIMABUKURO, Y. E.; SILVA, G. B. S. da; FREITAS, D. M. de. Comparative analysis of the global forest/non-forest maps derived from SAR and optical sensors: case studies from brazilian Amazon and Cerrado biomes. Remote Sensing, v. 13, n. 3, article 367, 2021.| Biblioteca(s): Embrapa Cerrados; Embrapa Meio Ambiente. |
| |
| 86. | | BOLFE, E. L.; BATISTELLA, M.; VICTORIA, D. de C.; CUSTODIO, D. de O.; SILVA, G. B. S. da; DRUCKER, D. P. Sistema de Observação e Monitoramento da Agricultura no Brasil. MundoGeo, Curitiba, v. 15, n. 75, p. 34-35, 2013.| Biblioteca(s): Embrapa Territorial. |
| |
| 88. | | SILVA, G. B. S. da; ARAUJO, L. S. de; NOGUEIRA, S. F.; BOLFE, E. L.; VICTORIA, D. de C.; VICENTE, L. E.; GREGO, C. R.; ANDRADE, R. G. Sistema de Informação Geográfica (SIG) e base de dados geoespaciais do projeto Geodegrade. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 16., 2013, Foz do Iguaçú. Anais... São José dos Campos: INPE, 2013. p. 2487-2493. 1 CD-ROM| Biblioteca(s): Embrapa Territorial. |
| |
| 89. | | KARVATTE JUNIOR, N.; MIYAGI, E. S.; OLIVEIRA, C. C. de; MASTELARO, A. P.; COELHO, F. de A.; SILVA, G. B. S. da; BUNGENSTAB, D. J.; ALVES, F. V. Spatiotemporal variations on infrared temperature as a thermal comfort indicator for cattle under agroforestry systems. Journal of Thermal Biology, v. 97, article 102871, 2021.| Biblioteca(s): Embrapa Meio Ambiente. |
| |
| 91. | | VICENTE, L. E.; LOEBMANN, D. G. dos S. W.; VICTORIA, D. de C.; GARCON, E. A. M.; BOLFE, E. L.; ANDRADE, R. G.; SILVA, G. B. S. da. Séries temporais de NDVI do sensor SPOT Vegetation e algoritmo SAM aplicados ao mapeamento de cana-de-açúcar. Pesquisa Agropecuária Brasileira, Brasilia, DF, v. 47, n. 9, p. 1337-1345, set. 2012.| Biblioteca(s): Embrapa Territorial; Embrapa Unidades Centrais. |
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| 92. | | LOEBMANN, D. G. dos S. W.; VICENTE, L. E.; GARCON, E. A. M.; SILVA, G. B. S. da; ANDRADE, R. G.; TORRESAN, F. E. Spectral angle mapping multitemporal approach in SPOT VEGETATION Time-Series to detect sugarcane areas in São Paulo State, Southeastern Brazil. In: AGU FALL MEETING, 2011, San Francisco. Anais... San Francisco: AGU, 2011.| Biblioteca(s): Embrapa Territorial. |
|  |
| 93. | | BULLER, L. S.; SILVA, G. B. S. da; ZANETTI, M. R.; ORTEGA, E.; MORAES, A. DE; GOULART, T.; BERGIER, I.; BULLER, L. S. Historical Land-Use Changes in São Gabriel do Oeste at the Upper Taquari River Basin. In: BERGIER, I.; ASSINE, M. L. (Ed.). Dynamics of the Pantanal Wetland in South America. Switzerland: Springer International Publishing, 2016. p. 191-208. (The Handbook of Environmental Chemistry, 37).| Biblioteca(s): Embrapa Pantanal. |
| |
| 94. | | VICTORIA, D. de C.; GARCON, E. A. M.; OLIVEIRA, B. P. de; SILVA, G. B. S. da; LOEBMANN, D. G. dos S. W. Geoprocessamento. In: TÔSTO, S. G.; RODRIGUES, C. A. G.; BOLFE, E. L.; BATISTELLA, M. (Ed.). Geotecnologias e geoinformação. Brasília, DF: Embrapa, 2014. p. 93-105. (Coleção 500 Perguntas, 500 Respostas)| Biblioteca(s): Embrapa Territorial. |
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| 95. | | GREGO, C. R.; MANJOLIN, R. C.; NOGUEIRA, S. F.; RODRIGUES, C. A. G.; SILVA, G. B. S. da; CONCEIÇÃO, M. P. C.; HERLING, V. R. Geostatistical Analysis of NDVI in rotational and continuous grazing pastures In: INTERNATIONAL SYMPOSIUM ON GREENHOUSE GASES IN AGRICULTURE, 2., 2016, Campo Grande, MS. Proceedings... Brasília, DF: Embrapa, 2016. p. 121-125. (Embrapa Gado de Corte. Documentos, 216).| Biblioteca(s): Embrapa Territorial. |
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| 96. | | VICTORIA, D. de C.; SILVA, G. B. S. da; NOGUEIRA, S. F.; VICENTE, L. E.; TAKEMURA, C. M.; GOMES, R. da C. Identificação de níveis de degradação de pastagem por meio de reflectância espectral de imagens de alta resolução espacial. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015. p. 1640-1647.| Biblioteca(s): Embrapa Territorial. |
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| 99. | | NOGUEIRA, S. F.; SILVA, G. B. S. da; MATEUS, G. P.; VICTORIA, D. de C.; ANDRADE, R. G.; DEMARCHI, J. J. A. DE A. Avaliação do modelo de mistura espectral com múltiplos componentes (MESMA) na discriminação de diferentes condições de cobertura em pastagens. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015. p. 2544-2551.| Biblioteca(s): Embrapa Territorial. |
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| 100. | | PAULA, S. C. DE; SILVA, G. B. S. da; VICENTE, L. E.; LOEBMANN, D. G. dos S. W.; NOGUEIRA, S. F.; ANDRADE, R. G. Avaliação de índices espectrais aplicados a série multitemporal TM/Landsat-5 para o mapeamento de fitofisionomias e pastagem em ambiente de cerrado. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 16., 2013, Foz do Iguaçú. Anais... São José dos Campos: INPE, 2013. p. 1790-1792. 1 CD-ROM| Biblioteca(s): Embrapa Territorial. |
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| Registros recuperados : 186 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Cerrados; Embrapa Meio Ambiente. |
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Data corrente: |
31/03/2021 |
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Data da última atualização: |
22/03/2022 |
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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: |
SANO, E. E.; RIZZOLI, P.; KOYAMA, C. N.; WATANABE, M.; ADAMI, M.; SHIMABUKURO, Y. E.; SILVA, G. B. S. da; FREITAS, D. M. de. |
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Afiliação: |
EDSON EYJI SANO, CPAC; PAOLA RIZOLLI, Microwaves and Radar Institute, German Aerospace Center; CHRISTIAN N KOYAMA, Tokyo Denki University; MANABU WATANABE, Tokyo Denki University; MARCOS ADAMI, INPE; YOSIO EDEMIR SHIMABUKURO, INPE; GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPMA; DANIEL MORAES DE FREITAS, IBAMA. |
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Título: |
Comparative analysis of the global forest/non-forest maps derived from SAR and optical sensors: case studies from brazilian Amazon and Cerrado biomes. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Remote Sensing, v. 13, n. 3, article 367, 2021. |
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DOI: |
https://doi.org/10.3390/rs13030367 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Global-scale forest/non-forest (FNF) maps are of crucial importance for applications like biomass estimation and deforestation monitoring. Global FNF maps based on optical remote sensing data have been produced by the wall-to-wall satellite image analyses or sampling strategies. The German Aerospace Center (DLR) and the Japan Aerospace Exploration Agency (JAXA) also made available their global FNF maps based on synthetic aperture radar (SAR) data. This paper attempted to answer the following scientific question: how comparable are the FNF products derived from optical and SAR data? As test sites we selected the Amazon (tropical rainforest) and Cerrado (tropical savanna) biomes, the two largest Brazilian biomes. Forest estimations from 2015 derived from TanDEM-X (X band; HH polarization) and ALOS-2 (L band; HV polarization) SAR data, as well as forest cover information derived from Landsat 8 optical data were compared with each other at the municipality and image sampling levels. The optical-based forest estimations considered in this study were derived from the MapBiomas project, a Brazilian multi-institutional project to map land use and land cover (LULC) classes of an entire country based on historical time series of Landsat data. In addition to the existing forest maps, a set of 1619 Landsat 8 RGB color composites was used to generate new independent comparison data composed of circular areas with 5-km diameter, which were visually interpreted after image segmentation. The Spearman rank correlation estimated the correlation among the data sets and the paired Mann–Whitney–Wilcoxon tested the hypothesis that the data sets are statistically equal. Results showed that forest maps derived from SAR and optical satellites are statistically different regardless of biome or scale of study (municipality or image sampling), except for the Cerrado´s forest estimations derived from TanDEM-X and ALOS-2. Nevertheless, the percentage of pixels classified as forest or non-forest by both SAR sensors were 90% and 80% for the Amazon and Cerrado biome, respectively, indicating an overall good agreement. MenosAbstract: Global-scale forest/non-forest (FNF) maps are of crucial importance for applications like biomass estimation and deforestation monitoring. Global FNF maps based on optical remote sensing data have been produced by the wall-to-wall satellite image analyses or sampling strategies. The German Aerospace Center (DLR) and the Japan Aerospace Exploration Agency (JAXA) also made available their global FNF maps based on synthetic aperture radar (SAR) data. This paper attempted to answer the following scientific question: how comparable are the FNF products derived from optical and SAR data? As test sites we selected the Amazon (tropical rainforest) and Cerrado (tropical savanna) biomes, the two largest Brazilian biomes. Forest estimations from 2015 derived from TanDEM-X (X band; HH polarization) and ALOS-2 (L band; HV polarization) SAR data, as well as forest cover information derived from Landsat 8 optical data were compared with each other at the municipality and image sampling levels. The optical-based forest estimations considered in this study were derived from the MapBiomas project, a Brazilian multi-institutional project to map land use and land cover (LULC) classes of an entire country based on historical time series of Landsat data. In addition to the existing forest maps, a set of 1619 Landsat 8 RGB color composites was used to generate new independent comparison data composed of circular areas with 5-km diameter, which were visually interpreted after image segmen... Mostrar Tudo |
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Palavras-Chave: |
ALOS-2; Forest mapping; SAR; TanDEM-X. |
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Thesagro: |
Cerrado; Floresta Tropical; Mapa; Sensoriamento Remoto. |
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Thesaurus NAL: |
Remote sensing; Savannas; Tropical forests. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/227779/1/Sano-comparative-analysis.pdf
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Marc: |
LEADER 03169naa a2200349 a 4500
001 2136157
005 2022-03-22
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/rs13030367$2DOI
100 1 $aSANO, E. E.
245 $aComparative analysis of the global forest/non-forest maps derived from SAR and optical sensors$bcase studies from brazilian Amazon and Cerrado biomes.$h[electronic resource]
260 $c2021
520 $aAbstract: Global-scale forest/non-forest (FNF) maps are of crucial importance for applications like biomass estimation and deforestation monitoring. Global FNF maps based on optical remote sensing data have been produced by the wall-to-wall satellite image analyses or sampling strategies. The German Aerospace Center (DLR) and the Japan Aerospace Exploration Agency (JAXA) also made available their global FNF maps based on synthetic aperture radar (SAR) data. This paper attempted to answer the following scientific question: how comparable are the FNF products derived from optical and SAR data? As test sites we selected the Amazon (tropical rainforest) and Cerrado (tropical savanna) biomes, the two largest Brazilian biomes. Forest estimations from 2015 derived from TanDEM-X (X band; HH polarization) and ALOS-2 (L band; HV polarization) SAR data, as well as forest cover information derived from Landsat 8 optical data were compared with each other at the municipality and image sampling levels. The optical-based forest estimations considered in this study were derived from the MapBiomas project, a Brazilian multi-institutional project to map land use and land cover (LULC) classes of an entire country based on historical time series of Landsat data. In addition to the existing forest maps, a set of 1619 Landsat 8 RGB color composites was used to generate new independent comparison data composed of circular areas with 5-km diameter, which were visually interpreted after image segmentation. The Spearman rank correlation estimated the correlation among the data sets and the paired Mann–Whitney–Wilcoxon tested the hypothesis that the data sets are statistically equal. Results showed that forest maps derived from SAR and optical satellites are statistically different regardless of biome or scale of study (municipality or image sampling), except for the Cerrado´s forest estimations derived from TanDEM-X and ALOS-2. Nevertheless, the percentage of pixels classified as forest or non-forest by both SAR sensors were 90% and 80% for the Amazon and Cerrado biome, respectively, indicating an overall good agreement.
650 $aRemote sensing
650 $aSavannas
650 $aTropical forests
650 $aCerrado
650 $aFloresta Tropical
650 $aMapa
650 $aSensoriamento Remoto
653 $aALOS-2
653 $aForest mapping
653 $aSAR
653 $aTanDEM-X
700 1 $aRIZZOLI, P.
700 1 $aKOYAMA, C. N.
700 1 $aWATANABE, M.
700 1 $aADAMI, M.
700 1 $aSHIMABUKURO, Y. E.
700 1 $aSILVA, G. B. S. da
700 1 $aFREITAS, D. M. de
773 $tRemote Sensing$gv. 13, n. 3, article 367, 2021.
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