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 | Acesso ao texto completo restrito à biblioteca da Embrapa Territorial. Para informações adicionais entre em contato com cnpm.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Territorial. |
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Data corrente: |
26/11/2015 |
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Data da última atualização: |
26/11/2015 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
FRANCESCHINI, M. H. D.; DEMATÊ, J. A. M.; VICENTE, L. E.; BARTHOLOMEUS, H.; SOUZA FILHO, C. R. DE. |
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Afiliação: |
M. H. D. FRANCESCHINI, USP; J. A. M. DEMATÊ, USP; LUIZ EDUARDO VICENTE, CNPM; H. BARTHOLOMEUS, WAGENING UNIVERSITY; C. R. DE SOUZA FILHO, UNICAMP. |
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Título: |
Prediction of soil properties using imaging spectroscopy: Considering fractional vegetation cover to improve accuracy. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
International Journal of Applied Earth Observation and Geoinformation, v. 38, p. 358-370, 2015. |
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DOI: |
http://dx.doi.org/10.1016/j.jag.2015.01.019 |
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Idioma: |
Inglês |
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Conteúdo: |
Spectroscopic techniques have become attractive to assess soil properties because they are fast, require little labor and may reduce the amount of laboratory waste produced when compared to conventional methods. Imaging spectroscopy (IS) can have further advantages compared to laboratory or field proximal spectroscopic approaches such as providing spatially continuous information with a high density. However, the accuracy of IS derived predictions decreases when the spectral mixture of soil with other targets occurs. This paper evaluates the use of spectral data obtained by an airborne hyperspectral sensor (ProSpecTIR-VS ? Aisa dual sensor) for prediction of physical and chemical properties of Brazilian highly weathered soils (i.e., Oxisols). A methodology to assess the soil spectral mixture is adapted and a progressive spectral dataset selection procedure, based on bare soil fractional cover, is proposed and tested. Satisfactory performances are obtained specially for the quantification of clay, sand and CEC using airborne sensor data (R2 of 0.77, 0.79 and 0.54; RPD of 2.14, 2.22 and 1.50, respectively), after spectral data selection is performed; although results obtained for laboratory data are more accurate (R2 of 0.92, 0.85 and 0.75; RPD of 3.52, 2.62 and 2.04, for clay, sand and CEC, respectively). Most importantly, predictions based on airborne-derived spectra for which the bare soil fractional cover is not taken into account show considerable lower accuracy, for example for clay, sand and CEC (RPD of 1.52, 1.64 and 1.16, respectively). Therefore, hyperspectral remotely sensed data can be used to predict topsoil properties of highly weathered soils, although spectral mixture of bare soil with vegetation must be considered in order to achieve an improved prediction accuracy. MenosSpectroscopic techniques have become attractive to assess soil properties because they are fast, require little labor and may reduce the amount of laboratory waste produced when compared to conventional methods. Imaging spectroscopy (IS) can have further advantages compared to laboratory or field proximal spectroscopic approaches such as providing spatially continuous information with a high density. However, the accuracy of IS derived predictions decreases when the spectral mixture of soil with other targets occurs. This paper evaluates the use of spectral data obtained by an airborne hyperspectral sensor (ProSpecTIR-VS ? Aisa dual sensor) for prediction of physical and chemical properties of Brazilian highly weathered soils (i.e., Oxisols). A methodology to assess the soil spectral mixture is adapted and a progressive spectral dataset selection procedure, based on bare soil fractional cover, is proposed and tested. Satisfactory performances are obtained specially for the quantification of clay, sand and CEC using airborne sensor data (R2 of 0.77, 0.79 and 0.54; RPD of 2.14, 2.22 and 1.50, respectively), after spectral data selection is performed; although results obtained for laboratory data are more accurate (R2 of 0.92, 0.85 and 0.75; RPD of 3.52, 2.62 and 2.04, for clay, sand and CEC, respectively). Most importantly, predictions based on airborne-derived spectra for which the bare soil fractional cover is not taken into account show considerable lower accuracy, for exam... Mostrar Tudo |
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Palavras-Chave: |
Hyperspectral; Pedometrics; Unmixing analysis. |
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Thesaurus Nal: |
Reflectance spectroscopy; Soil properties. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02646naa a2200241 a 4500
001 2029643
005 2015-11-26
008 2015 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1016/j.jag.2015.01.019$2DOI
100 1 $aFRANCESCHINI, M. H. D.
245 $aPrediction of soil properties using imaging spectroscopy$bConsidering fractional vegetation cover to improve accuracy.$h[electronic resource]
260 $c2015
520 $aSpectroscopic techniques have become attractive to assess soil properties because they are fast, require little labor and may reduce the amount of laboratory waste produced when compared to conventional methods. Imaging spectroscopy (IS) can have further advantages compared to laboratory or field proximal spectroscopic approaches such as providing spatially continuous information with a high density. However, the accuracy of IS derived predictions decreases when the spectral mixture of soil with other targets occurs. This paper evaluates the use of spectral data obtained by an airborne hyperspectral sensor (ProSpecTIR-VS ? Aisa dual sensor) for prediction of physical and chemical properties of Brazilian highly weathered soils (i.e., Oxisols). A methodology to assess the soil spectral mixture is adapted and a progressive spectral dataset selection procedure, based on bare soil fractional cover, is proposed and tested. Satisfactory performances are obtained specially for the quantification of clay, sand and CEC using airborne sensor data (R2 of 0.77, 0.79 and 0.54; RPD of 2.14, 2.22 and 1.50, respectively), after spectral data selection is performed; although results obtained for laboratory data are more accurate (R2 of 0.92, 0.85 and 0.75; RPD of 3.52, 2.62 and 2.04, for clay, sand and CEC, respectively). Most importantly, predictions based on airborne-derived spectra for which the bare soil fractional cover is not taken into account show considerable lower accuracy, for example for clay, sand and CEC (RPD of 1.52, 1.64 and 1.16, respectively). Therefore, hyperspectral remotely sensed data can be used to predict topsoil properties of highly weathered soils, although spectral mixture of bare soil with vegetation must be considered in order to achieve an improved prediction accuracy.
650 $aReflectance spectroscopy
650 $aSoil properties
653 $aHyperspectral
653 $aPedometrics
653 $aUnmixing analysis
700 1 $aDEMATÊ, J. A. M.
700 1 $aVICENTE, L. E.
700 1 $aBARTHOLOMEUS, H.
700 1 $aSOUZA FILHO, C. R. DE
773 $tInternational Journal of Applied Earth Observation and Geoinformation$gv. 38, p. 358-370, 2015.
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Registro original: |
Embrapa Territorial (CNPM) |
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Registro Completo
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Biblioteca(s): |
Embrapa Mandioca e Fruticultura. |
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Data corrente: |
03/09/2014 |
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Data da última atualização: |
25/05/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
SANTOS, MARCELO R. dos; MARTINEZ, M. A.; DONATO, S. L. R.; COELHO, E. F. |
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Afiliação: |
MARCELO R. DOS SANTOS, UFV; MAURO A. MARTINEZ, IF BAIANO; SÉRGIO L. R. DONATO, UFV; EUGENIO FERREIRA COELHO, CNPMF. |
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Título: |
'Tommy Atkins' mango yield and photosynthesis under water deficit in semiarid region of Bahia. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Revista Brasileira de Engenharia Agrícola e Ambiental, v.18, n.9, p.899-907, 2014. |
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ISSN: |
1807-1929 |
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Idioma: |
Inglês |
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Conteúdo: |
The aim of this study was to evaluate the 'Tommy Atkins' mango yield and photosynthesis in regulated deficit irrigation (RDI) in semiarid conditions of Bahia, Brazil. The experimental design was a randomized block with five treatments and six replications: T1, irrigation supplying 100% crop evapotranspiration (ETc) in phases: I (beginning of flowering to early fruit growth), II (start of expansion until early physiological maturity) and phase III (physiologically mature fruits); T2, RDI with 50% ETc in phase I; T3, RDI with 50% ETc in phase II; T4, RDI with 50% ETc in phase III; T5, No irrigation. The soil water deficit causes a reduction in photosynthesis. Mango yield in treatment 4 was approximately 5.5 and 2 times greater than in treatments 5 and 2, respectively. The use of RDI with 50% water depth reduction applied in the third phase of 'Tommy Atkins' mango fruit development was efficient. The use of RDI with 50% ETc in the third phase of fruit development provided the best yield of 'Tommy Atkins' mango for the 350 g weight class. |
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Thesagro: |
Irrigação; Manga. |
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Thesaurus NAL: |
Irrigation; Mangoes. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01705naa a2200217 a 4500
001 1994180
005 2023-05-25
008 2014 bl uuuu u00u1 u #d
022 $a1807-1929
100 1 $aSANTOS, MARCELO R. dos
245 $a'Tommy Atkins' mango yield and photosynthesis under water deficit in semiarid region of Bahia.$h[electronic resource]
260 $c2014
520 $aThe aim of this study was to evaluate the 'Tommy Atkins' mango yield and photosynthesis in regulated deficit irrigation (RDI) in semiarid conditions of Bahia, Brazil. The experimental design was a randomized block with five treatments and six replications: T1, irrigation supplying 100% crop evapotranspiration (ETc) in phases: I (beginning of flowering to early fruit growth), II (start of expansion until early physiological maturity) and phase III (physiologically mature fruits); T2, RDI with 50% ETc in phase I; T3, RDI with 50% ETc in phase II; T4, RDI with 50% ETc in phase III; T5, No irrigation. The soil water deficit causes a reduction in photosynthesis. Mango yield in treatment 4 was approximately 5.5 and 2 times greater than in treatments 5 and 2, respectively. The use of RDI with 50% water depth reduction applied in the third phase of 'Tommy Atkins' mango fruit development was efficient. The use of RDI with 50% ETc in the third phase of fruit development provided the best yield of 'Tommy Atkins' mango for the 350 g weight class.
650 $aIrrigation
650 $aMangoes
650 $aIrrigação
650 $aManga
700 1 $aMARTINEZ, M. A.
700 1 $aDONATO, S. L. R.
700 1 $aCOELHO, E. F.
773 $tRevista Brasileira de Engenharia Agrícola e Ambiental$gv.18, n.9, p.899-907, 2014.
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Embrapa Mandioca e Fruticultura (CNPMF) |
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