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| Registros recuperados : 64 | |
| 7. |  | SANO, E. E.; GIAROLLA, A.; ADAMI, M.; JACKSON, T. J. Calibração da estimativa superficial de solos do Cerrado. In: ANDRADE, S. R. M. de; FALEIRO, F. G.; SERENO, J. R.; DALLA CORTE, J. L.; SOUSA, E. dos S. de (Ed.). Resultados de pesquisa para o Cerrado: 2004-2005. Planaltina, DF: Embrapa Cerrados, 2007. p. 79-82.| Biblioteca(s): Embrapa Cerrados. |
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| 10. | | SUGAWARA, L. M.; RUDORFF, B. F. T.; ADAMI, M. Viabilidade de uso de imagens do Landsat em mapeamento de área cultivada com soja no Estado do Paraná. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 43, n. 12, p. 1777-1783, dez. 2008. Título em inglês: Feasibility of the use of Landsat imagery to map soybean crop areas in Paraná, Brazil.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 11. | | SADECK, L. W. R.; LIMA, A. M. M. de; ADAMI, M. Artificial neural network for ecological-economic zoning as a tool for spatial planning. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 52, n, 11, p. 1050-1062, novembro 2017. Título em português: Rede neural artificial para o zoneamento ecológico-econômico como instrumento de ordenamento territorial.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 12. | | ADAMI, M.; RIZZI, R.; MOREIRA, M. A.; RUDORFF, B. F. T.; FERREIRA, C. C. Amostragem probabilística estratificada por pontos para estimar a área cultivada com soja. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 45, n. 6, p. 585-592, jun. 2010 Título em inglês: Probabilistic stratified point sampling to estimate soybean crop area.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 14. | | GUSSO, A.; FORMAGGIO, A. R.; RIZZI, R.; ADAMI, M.; RUDORFF, B. F. T. Soybean crop area estimation by Modis/Evi data. Pesquisa Agropecuaria Brasileira, Brasília, DF, v. 47, n. 3, p. 425-435, mar. 2012. Título em português: Estimativa de áreas de cultivo de soja por meio de dados Modis/Evi.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 15. | | PADOVANI, C. R.; SHIMABUKURO, Y. E.; FREITAS, R. M.; ADAMI, M.; VETTORAZZI, C. A. Spatial analysis of Pantanal wetland flood dynamics determined from modis images: a case study . In: INTECOL INTERNATIONAL WETLANDS CONFERENCE, 8., Cuiabá, 2008. Big wetlands, big concerns: abstracts. [Sl.: s.n], 2008. p.160| Biblioteca(s): Embrapa Pantanal. |
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| 16. | | SILVA, G. B. S. da; FORMAGGIO, A. R.; SHIMABUKURO, Y. E.; ADAMI, M.; SANO, E. E. Discriminação da cobertura vegetal do Cerrado matogrossense por meio de imagens MODIS. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 45, n. 2, p. 186-194, fev. 2010 Título em inglês: Discrimination of Cerrado vegetation cover in the state of Mato Grosso using MODIS images.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 20. | | ROSA, V. G. C. da; MOREIRA, M. A.; RUDOFF, B. F. T.; ADAMI, M. Estimativa da produtividade de café com base em um modelo agrometeorológico-espectral. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 45, n. 12, p. 1478-1488, dez. 2010 Título em inglês: Coffee crop yield estimate using an agrometeorological?spectral model.| Biblioteca(s): Embrapa Unidades Centrais. |
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| Registros recuperados : 64 | |
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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
|
|
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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