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| Registros recuperados : 9 | |
| 1. |  | JONATHAN, M.; MEIRELLES, M.; BERROIR, J.-P.; HERLIN, I. Considerações para o monitoramento do uso do solo com dados MODIS para longos períodos e em escala regional, e sua aplicação na bacia do Alto Taquari, MS/MT. Revista Brasileira de Cartografia, Rio de Janeiro, v. 59, n. 1, p. 1-7, abr. 2007.| Biblioteca(s): Embrapa Solos. |
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| 3. | | ARVOR, D.; MEIRELLES, M.; MARTORANO, L. G.; JONATHAN, M.; DUBREUIL, V.; HERLIN, I.; BERROIR, J.-P. Séries temporais de EVI/MODIS na identificação da dinâmica da soja em sistema plantio direto no Mato Grosso, Brasil. In: REUNIÃO BRASILEIRA DE MANEJO E CONSERVAÇÃO DO SOLO E DA ÁGUA, 17., 2008, Rio de Janeiro. Manejo e conservação do solo e da água no contexto das mudanças ambientais. Rio de Janeiro: Embrapa Solos, 2008. 1 CD-ROM. (Embrapa Solos. Documentos, 101).| Biblioteca(s): Embrapa Solos. |
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| 4. | | JONATHAN, M.; MEIRELLES, M. S. P.; BERROIR, J.-P.; HERLIN, I. Considerações para o monitoramento do uso do solo com dados modis para longos períodos e em escala regional, e sua aplicação na Bacia do Alto Taquari, MS/MT. Revista Brasileira de Cartografia, Rio de Janeiro, v. 59, n. 1, p. 1-7, 2007.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 6. | | COSTA, G. A. O. P. da; SIMÕES, M.; SINGH, D.; HERLIN, I.; BERROIR, J. P.; SILVA, E. F. da. A methodology to support environmental degradation monitoring and analysis using AVHRR data. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 12., 2005, Goiânia. Anais [...]. São José dos Campos: INPE, 2005. p. 2941-2948.| Biblioteca(s): Embrapa Solos. |
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| 7. | | ARVOR, D.; MEIRELLES, M. S. P.; VARGAS, R.; SKORUPA, L. A.; FIDALGO, E. C. C.; DUBREUIL, V.; BERROIR, J.-P. Monitoring land use changes around the indigenous lands of the Xingu basin in Mato Grosso, Brasil. In: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, Honolulu, HI. Proceedings... Danvers, MA: IEEE, 2010. p. 3190-3193.| Biblioteca(s): Embrapa Solos. |
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| 8. | | SINGH, D.; MEIRELLES, M. S. P.; COSTA, G. A.; HERLIN, I.; BERROIR, J. P.; SILVA, E. F. Environmental degradation analysis using NOAA/AVHRR data. Advances in Space Research, v. 37, n. 4, p. 720-727, 2006.| Biblioteca(s): Embrapa Solos. |
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| 9. | | SIMÕES, M.; COSTA, G. A. P.; SINGH, D.; SINGH, K. P.; COUTINHO, H. L. da C.; FRAGA, E.; BERROIR, J. P.; HERLIN, I.; VIEIRA, H. V.; SANTOS, U. P. Remote sensing and spatial decision support system for environmental degradation monitoring. In: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2003, Toulouse. Proceedings... Piscataway: IEEE, 2003. v. 3, p. 2088-2090. IGARSS 2003.| Biblioteca(s): Embrapa Solos. |
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| Registros recuperados : 9 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
07/10/2021 |
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Data da última atualização: |
08/10/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
SINGH, D.; MEIRELLES, M. S. P.; COSTA, G. A.; HERLIN, I.; BERROIR, J. P.; SILVA, E. F. |
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Afiliação: |
D. SINGH, Indian Institute of Technology; MARGARETH GONCALVES SIMOES, CNPS; G. A. COSTA, UERJ; I. HERLIN, Institut National de Recherche en Informatique et Automatique; J. P. BERROIR, Institut National de Recherche en Informatique et Automatique; E. F. SILVA, CNPS. |
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Título: |
Environmental degradation analysis using NOAA/AVHRR data. |
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Ano de publicação: |
2006 |
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Fonte/Imprenta: |
Advances in Space Research, v. 37, n. 4, p. 720-727, 2006. |
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DOI: |
https://doi.org/10.1016/j.asr.2004.12.052 |
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Idioma: |
Inglês |
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Conteúdo: |
This paper proposes a particular approach to assess information about soil degradation, based on a methodology to calculate soil color from NOAA/AVHRR data. As erosive processes change physical and chemical properties of the soil, altering, consequently, the superficial color, monitoring the change in color over time can help to identify and analyze those processes. A relationship among the soil color (described in the Munsell Color System, i.e., in terms of Hue, Value and Chroma), vegetation indices, surface temperature and emissivity has been established, which is based on the theoretical model. The methodology has three main phases: determination of the regression models among soil color and vegetation indices, emissivity and surface temperature; generation of digital soil color models; and statistical evaluation of the estimated color. The tests showed that the methodology is efficient in determining soil color using the various vegetation indices (i.e., Normalized vegetation index NDVI, Modified soil adjusted vegetation index MSAVI). One vegetation index, i.e., Purified adjusted vegetation index (PAVI) is proposed to subsidies the effect of vegetation over the soil. Best results were obtained for the Hue color component. To further test the methodology, the estimated digital color models were compared with the characteristic color of soil classes in the test area. The results of this application confirmed the methodology's capacity to determine the soil color from NOAA/AVHRR data. This type of study is quite helpful to know the erosion of soil as well as some abrupt change in soil due to natural hazards by space borne or air-borne sensors. MenosThis paper proposes a particular approach to assess information about soil degradation, based on a methodology to calculate soil color from NOAA/AVHRR data. As erosive processes change physical and chemical properties of the soil, altering, consequently, the superficial color, monitoring the change in color over time can help to identify and analyze those processes. A relationship among the soil color (described in the Munsell Color System, i.e., in terms of Hue, Value and Chroma), vegetation indices, surface temperature and emissivity has been established, which is based on the theoretical model. The methodology has three main phases: determination of the regression models among soil color and vegetation indices, emissivity and surface temperature; generation of digital soil color models; and statistical evaluation of the estimated color. The tests showed that the methodology is efficient in determining soil color using the various vegetation indices (i.e., Normalized vegetation index NDVI, Modified soil adjusted vegetation index MSAVI). One vegetation index, i.e., Purified adjusted vegetation index (PAVI) is proposed to subsidies the effect of vegetation over the soil. Best results were obtained for the Hue color component. To further test the methodology, the estimated digital color models were compared with the characteristic color of soil classes in the test area. The results of this application confirmed the methodology's capacity to determine the soil color from NOAA/... Mostrar Tudo |
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Thesaurus NAL: |
Remote sensing; Soil color; Soil erosion. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02332naa a2200229 a 4500
001 2135164
005 2021-10-08
008 2006 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.asr.2004.12.052$2DOI
100 1 $aSINGH, D.
245 $aEnvironmental degradation analysis using NOAA/AVHRR data.$h[electronic resource]
260 $c2006
520 $aThis paper proposes a particular approach to assess information about soil degradation, based on a methodology to calculate soil color from NOAA/AVHRR data. As erosive processes change physical and chemical properties of the soil, altering, consequently, the superficial color, monitoring the change in color over time can help to identify and analyze those processes. A relationship among the soil color (described in the Munsell Color System, i.e., in terms of Hue, Value and Chroma), vegetation indices, surface temperature and emissivity has been established, which is based on the theoretical model. The methodology has three main phases: determination of the regression models among soil color and vegetation indices, emissivity and surface temperature; generation of digital soil color models; and statistical evaluation of the estimated color. The tests showed that the methodology is efficient in determining soil color using the various vegetation indices (i.e., Normalized vegetation index NDVI, Modified soil adjusted vegetation index MSAVI). One vegetation index, i.e., Purified adjusted vegetation index (PAVI) is proposed to subsidies the effect of vegetation over the soil. Best results were obtained for the Hue color component. To further test the methodology, the estimated digital color models were compared with the characteristic color of soil classes in the test area. The results of this application confirmed the methodology's capacity to determine the soil color from NOAA/AVHRR data. This type of study is quite helpful to know the erosion of soil as well as some abrupt change in soil due to natural hazards by space borne or air-borne sensors.
650 $aRemote sensing
650 $aSoil color
650 $aSoil erosion
700 1 $aMEIRELLES, M. S. P.
700 1 $aCOSTA, G. A.
700 1 $aHERLIN, I.
700 1 $aBERROIR, J. P.
700 1 $aSILVA, E. F.
773 $tAdvances in Space Research$gv. 37, n. 4, p. 720-727, 2006.
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