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| 1. |  | FRANCO, A. A.; CAMPELLO, E. F. C.; FARIA, S. M. de; DIAS, L. E.; CASTILHO, A. F. de; FORTES, J. L. de O.; CAMPOS NETO, D.; CERQUEIRA, L. S.; MOREIRA, J. F.; RESENDE, A. S. de. Revegetação de áreas degradadas pela mineração e processamento de bauxita. In: ALVA, J. M. F. Recuperação de áreas mineradas: a visão dos especialistas brasileiros. Pelotas: Embrapa Clima Temperado, 2007. p. 201-212. Parceria: UFV; Mineração Rio do Norte; Universidade Estadual do Maranhão; Alumar-MA; Alunorte; UFRRJ.| Biblioteca(s): Embrapa Agrobiologia. |
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| 2. | | FRANCO, A. A.; CAMPELLO, E. F. C.; FARIA, S. M. de; DIAS, L. E.; CASTILHO, A. F. de; FORTES, J. L. de O.; CAMPOS NETO, D.; CERQUEIRA, L. S.; MOREIRA, J. F.; RESENDE, A. S. de. Revegetação de áreas degradadas pela mineração e processamento de bauxita. In:FILIPPINI ALBA, J. M. (Ed.). Recuperação de áreas mineradas. 2.ed.rev. Brasília, DF: Embrapa Informação Tecnológica; Pelotas: Embrapa Clima Temperado, 2010. 326 p. il. p. 303-321| Biblioteca(s): Embrapa Agrobiologia. |
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| Registros recuperados : 2 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
04/10/2019 |
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Data da última atualização: |
04/10/2019 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
OLIVEIRA, R. P. de; RODRIGUES, H. M.; VASQUES, G. de M.; TAVARES, S. R. de L.; HERNANI, L. C.; BACA, J. F. M.; COELHO, M. R. |
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Afiliação: |
RONALDO PEREIRA DE OLIVEIRA, CNPS; HUGO M. RODRIGUES, UFRRJ; GUSTAVO DE MATTOS VASQUES, CNPS; SILVIO ROBERTO DE LUCENA TAVARES, CNPS; LUIS CARLOS HERNANI, CNPS; JESUS FERNANDO MANSILLA BACA, CNPS; MAURICIO RIZZATO COELHO, CNPS. |
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Título: |
Proximal soil sensing platform for effective mapping of soil attributes in Brazil. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
In: GLOBAL WORKSHOP ON PROXIMAL SOIL SENSING, 5., 2019, Columbia, MO. Program and proceedings. Columbia, MO: University of Missouri, 2019. p. 273-278. |
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Idioma: |
Inglês |
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Conteúdo: |
Sustainable management of agricultural lands requires detailed information on soil properties. Although the literature has shown the potential of PSS data integration to predict spatial variations of soil properties, most of these studies were done in temperate soils considering up to three sensors. Study cases here introduced to contribute in applying PSS to: (i) assess the spatial variation of tropical soil chemical and physical attributes; (ii) understand processes controlling spatial soil variations; and (iii) compare spatial dependence and patterns among proximally-sensed and laboratory-measured soil attributes. In three preliminary study cases PSS was applied for digital soil mapping, soil salinity mapping, and within-field crop variations. Hand held and "on-the-go" sensors, respectively, for point-based and continuous monitoring readings, include apparent electrical conductivity and magnetic susceptibility meters; gamma ray, X-ray fluorescence and near infrared spectrometers; and mechanical resistance meters among others. Variables were significantly correlated (p < 0.05), and their spatial dependence structure (i.e: variogram analysis) and the spatial distribution patterns (i.e.: kriging) were all-similar. In addition, combined PSS datasets have shown improved predictions of soil properties (i.e.: R2adj. from 0.21 to 0.94). Results have indicated the potential of PSS to assess the spatial variation of soil attributes that are more difficult to collect and analyze, supporting detailed soil mapping for precision agriculture and related activities. MenosSustainable management of agricultural lands requires detailed information on soil properties. Although the literature has shown the potential of PSS data integration to predict spatial variations of soil properties, most of these studies were done in temperate soils considering up to three sensors. Study cases here introduced to contribute in applying PSS to: (i) assess the spatial variation of tropical soil chemical and physical attributes; (ii) understand processes controlling spatial soil variations; and (iii) compare spatial dependence and patterns among proximally-sensed and laboratory-measured soil attributes. In three preliminary study cases PSS was applied for digital soil mapping, soil salinity mapping, and within-field crop variations. Hand held and "on-the-go" sensors, respectively, for point-based and continuous monitoring readings, include apparent electrical conductivity and magnetic susceptibility meters; gamma ray, X-ray fluorescence and near infrared spectrometers; and mechanical resistance meters among others. Variables were significantly correlated (p < 0.05), and their spatial dependence structure (i.e: variogram analysis) and the spatial distribution patterns (i.e.: kriging) were all-similar. In addition, combined PSS datasets have shown improved predictions of soil properties (i.e.: R2adj. from 0.21 to 0.94). Results have indicated the potential of PSS to assess the spatial variation of soil attributes that are more difficult to collect and analyze, su... Mostrar Tudo |
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Palavras-Chave: |
Atributos do Solo; Mapeamento Digital do Solo; Sensoriamento Proximal. |
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Thesagro: |
Mapa; Sensoriamento Remoto; Solo Tropical. |
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Thesaurus NAL: |
Digital images; Remote sensing; Soil map; Tropical soils. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/202570/1/Proximal-Soil-Sensing-Platform-for-Effective-Mapping-of-Soil-Attributes-in-Brazil-2019.pdf
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Marc: |
LEADER 02568nam a2200301 a 4500
001 2112779
005 2019-10-04
008 2019 bl uuuu u00u1 u #d
100 1 $aOLIVEIRA, R. P. de
245 $aProximal soil sensing platform for effective mapping of soil attributes in Brazil.$h[electronic resource]
260 $aIn: GLOBAL WORKSHOP ON PROXIMAL SOIL SENSING, 5., 2019, Columbia, MO. Program and proceedings. Columbia, MO: University of Missouri, 2019. p. 273-278.$c2019
520 $aSustainable management of agricultural lands requires detailed information on soil properties. Although the literature has shown the potential of PSS data integration to predict spatial variations of soil properties, most of these studies were done in temperate soils considering up to three sensors. Study cases here introduced to contribute in applying PSS to: (i) assess the spatial variation of tropical soil chemical and physical attributes; (ii) understand processes controlling spatial soil variations; and (iii) compare spatial dependence and patterns among proximally-sensed and laboratory-measured soil attributes. In three preliminary study cases PSS was applied for digital soil mapping, soil salinity mapping, and within-field crop variations. Hand held and "on-the-go" sensors, respectively, for point-based and continuous monitoring readings, include apparent electrical conductivity and magnetic susceptibility meters; gamma ray, X-ray fluorescence and near infrared spectrometers; and mechanical resistance meters among others. Variables were significantly correlated (p < 0.05), and their spatial dependence structure (i.e: variogram analysis) and the spatial distribution patterns (i.e.: kriging) were all-similar. In addition, combined PSS datasets have shown improved predictions of soil properties (i.e.: R2adj. from 0.21 to 0.94). Results have indicated the potential of PSS to assess the spatial variation of soil attributes that are more difficult to collect and analyze, supporting detailed soil mapping for precision agriculture and related activities.
650 $aDigital images
650 $aRemote sensing
650 $aSoil map
650 $aTropical soils
650 $aMapa
650 $aSensoriamento Remoto
650 $aSolo Tropical
653 $aAtributos do Solo
653 $aMapeamento Digital do Solo
653 $aSensoriamento Proximal
700 1 $aRODRIGUES, H. M.
700 1 $aVASQUES, G. de M.
700 1 $aTAVARES, S. R. de L.
700 1 $aHERNANI, L. C.
700 1 $aBACA, J. F. M.
700 1 $aCOELHO, M. R.
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