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| Registros recuperados : 132 | |
| 81. |  | GRUNWALD, S.; CHAIKAEW, P.; CAO, B.; XIONG, X.; VASQUES, G. M.; KIM, J.; ROSS, C. W.; CLINGENSMITH, C. M.; XU, Y.; GAVILAN, C. The meta soil model: an integrative framework to model soil carbon across various ecosystems and scales. In: ZHANG, G.-L.; BRUS, D.; LIU, F.; SONG, X.-D.; LAGACHERIE, P. (Ed.). Digital soil mapping across paradigms, scales and boundaries. New York: Springer, 2016. cap. 14, p. 165-179.| Biblioteca(s): Embrapa Solos. |
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| 83. | | VASQUES, G. de M.; RODRIGUES, H. M.; COELHO, M. R.; BACA, J. F. M.; DART, R. de O.; OLIVEIRA, R. P. de; TEIXEIRA, W. G.; CEDDIA, M. B. Field proximal soil sensor fusion for improving high-resolution soil property maps. Soil Systems, v. 4, n. 3, 52, 2020.| Biblioteca(s): Embrapa Solos. |
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| 84. | | RODRIGUES, H. M.; VASQUES, G. de M.; OLIVEIRA, R. P. de; TAVARES, S. R. de L.; CEDDIA, M. B.; HERNANI, L. C. Finding suitable transect spacing and sampling designs for accurate soil ECa mapping from EM38-MK2. Soil Systems, v. 4, n. 3, 56, 2020.| Biblioteca(s): Embrapa Solos. |
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| 86. | | NASCIMENTO, C. W. R. do; RODRIGUES, H. M.; CEDDIA, M. B.; VASQUES, G. de M.; DURÃO, S. M. de O.; FIGUEIRA, H. F. V. Identificação de limites entre duas classes de solo utilizando radar de penetração no solo com profundidades ajustadas por barras de ferro e validação com trado holandês. In: SIMPÓSIO BRASILEIRO DE GEOGRAFIA FÍSICA APLICADA, 18., 2019, Fortaleza. Geografia física e as mudanças globais. Fortaleza: Editora UFC, 2019.| Biblioteca(s): Embrapa Solos. |
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| 88. | | VASQUES, G. de M.; RODRIGUES, H. M.; HUBER, E.; TAVARES, S. R. de L.; MARQUES, F. A.; SILVA, M. S. L. da. Ground penetrating radar non-invasively positions an underground dam and estimates its water reservoir shape and volume. In: PEDOMETRICS BRAZIL, 2., 2021, Rio de Janeiro. Annals [...]. Rio de Janeiro: Embrapa Solos, 2022. Não paginado. Evento online.| Biblioteca(s): Embrapa Solos. |
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| 89. | | MARTINS, A. M. M.; CARVALHO JUNIOR, W. de; DART, R. de O.; BHERING, S. B.; VASQUES, G. M.; PEREIRA, N. R.; CHAGAS, C. da S. Geração de imagem média na plataforma GEE para o município de Rio Brilhante (MS). In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 20., 2023, Florianópolis. Anais [...]. São José dos Campos: Instituto Nacional de Pesquisas Espaciais, 2023. p. 785-788.| Biblioteca(s): Embrapa Solos. |
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| 90. | | NASCIMENTO, C. W. R. do; RODRIGUES, H. M.; CEDDIA, M. B.; VASQUES, G. de M.; DURÃO, S. M. de O.; SANTOS, W. de M.; FREIRE, M. de O. Identificação em profundidade de barras de ferro utilizando radar de penetração do solo (GPR) com antena de 450 MHz em três classes de solo. In: SIMPÓSIO BRASILEIRO DE GEOGRAFIA FÍSICA APLICADA, 18., 2019, Fortaleza. Geografia física e as mudanças globais. Fortaleza: Editora UFC, 2019.| Biblioteca(s): Embrapa Solos. |
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| 91. | | VASQUES, G. M.; DEMATTÊ, J. A. M.; VISCARRA ROSSEL, R. A.; RAMÍREZ LÓPEZ, S.; TERRA, F. S.; RIZZO, R.; SOUZA FILHO, C. R. de. Integrating geospatial and multi-depth laboratory spectral data for mapping soil classes in a geologically complex area in southeastern Brazil. European Journal of Soil Science, v. 66, n. 4, p. 767-779, Jul. 2015.| Biblioteca(s): Embrapa Solos. |
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| 92. | | FERREIRA, A. C. de S.; CEDDIA, M. B.; COSTA, E. M.; PINHEIRO, E. F. M.; NASCIMENTO, M. M. do; VASQUES, G. M. Use of airborne radar images and machine learning algorithms to map soil clay, silt, and sand contents in remote areas under the Amazon rainforest. Remote Sensing, v. 14, n. 22, 5711, 2022.| Biblioteca(s): Embrapa Solos. |
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| 93. | | HOOVER, B.; GRUNWALD, S.; MARTIN, T. A.; VASQUES, G. M.; KNOX, N. M.; KIM, J.; XIONG, X.; CHAIKAEW, P.; ADEWOPO, J.; CAO, B.; ROSS, C. W. The Terrestrial Carbon (Terra C) Information System to facilitate carbon synthesis across heterogeneous landscapes. In: INTERNATIONAL ANNUAL MEETINGS, 2011, San Antonio. Anais... San Antonio: ASA/CSSA/SSSA, 2011.| Biblioteca(s): Embrapa Solos. |
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| 94. | | LONDRES, V. R.; RODRIGUES, T. F.; VASQUES, G. M.; TAVARES, S. R. de L.; MARQUES, F. A.; OLIVEIRA NETO, M. B. de; SILVA, M. S. L. da. Uso da extensão Arc Hydro e MDE Copernicus de 30 m para delinear a drenagem e delimitar microbacias tributárias do Rio Ipanema, AL/PE. In: SIMPÓSIO BRASILEIRO DE RECURSOS HÍDRICOS, 25., 2023, Aracaju. Anais [...]. Porto Alegre: Associação Brasileira de Recursos Hídricos, 2023. Ref. XXV-SBRH0887.| Biblioteca(s): Embrapa Solos. |
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| 95. | | RODRIGUES, H. M.; NASCIMENTO, C. W. R. do; CEDDIA, M. B.; VASQUES, G. de M.; NUNES, J. F.; SANTOS, F. B. dos. Uso de barras de ferro para diferenciação entre horizontes de três classes de solo utilizando radar de penetração do solo (GPR) com antena monoestática de 750 MHz. In: SIMPÓSIO BRASILEIRO DE GEOGRAFIA FÍSICA APLICADA, 18., 2019, Fortaleza. Geografia física e as mudanças globais. Fortaleza: Editora UFC, 2019.| Biblioteca(s): Embrapa Solos. |
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| 96. | | 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. Proximal soil sensing platform for effective mapping of soil attributes in Brazil. In: GLOBAL WORKSHOP ON PROXIMAL SOIL SENSING, 5., 2019, Columbia, MO. Program and proceedings. Columbia, MO: University of Missouri, 2019. p. 273-278.| Biblioteca(s): Embrapa Solos. |
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| 97. | | LÁZARO, M. L.; VASQUES, G. de M.; MATA, M. G. F. da; GUERRA, J. G. M.; CEDDIA, M. B.; PINHEIRO, E. F. M. Qualitative evaluation of soil organic matter using Vis-NIR diffuse reflectance spectroscopy in an agroecological production system in Seropédica, Rio de Janeiro (Brazil). In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: proceedings... Viçosa, MG: SBCS, 2019. v. 2, p. 536. WCSS 2018.| Biblioteca(s): Embrapa Agrobiologia; Embrapa Solos. |
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| 98. | | LAZARO, M. L.; VASQUES, G. M.; MATA, M. G. F. da; GUERRA, J. G. M.; CEDDIA, M. B.; PINHERO, E. F. M. Qualitative evaluation of soil organic matter using VisNIR diffuse reflectance spectroscopy in an agroecological production system in Seropédica, Rio de Janeiro (Brazil). In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Soil science: beyond food and fuel: proceedings... Viçosa, MG: SBCS, 2019 v. 2. p. 536 WCSS 2018.| Biblioteca(s): Embrapa Agrobiologia. |
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| Registros recuperados : 132 | |
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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: |
25/08/2016 |
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Data da última atualização: |
25/08/2016 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
GRUNWALD, S.; CHAIKAEW, P.; CAO, B.; XIONG, X.; VASQUES, G. M.; KIM, J.; ROSS, C. W.; CLINGENSMITH, C. M.; XU, Y.; GAVILAN, C. |
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Afiliação: |
S. GRUNWALD, UNIVERSITY OF FLORIDA; P. CHAIKAEW, Chulalongkorn University; B. CAO, UNIVERSITY OF FLORIDA; X. XIONG, UNIVERSITY OF FLORIDA; GUSTAVO DE MATTOS VASQUES, CNPS; J. KIM, Chungnam National University; C. W. ROSS, UNIVERSITY OF FLORIDA; C. M. CLINGENSMITH, UNIVERSITY OF FLORIDA; Y. XU, UNIVERSITY OF FLORIDA; C. GAVILAN, UNIVERSITY OF FLORIDA. |
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Título: |
The meta soil model: an integrative framework to model soil carbon across various ecosystems and scales. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
In: ZHANG, G.-L.; BRUS, D.; LIU, F.; SONG, X.-D.; LAGACHERIE, P. (Ed.). Digital soil mapping across paradigms, scales and boundaries. New York: Springer, 2016. cap. 14, p. 165-179. |
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Idioma: |
Inglês |
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Conteúdo: |
Over the past decades, a changing climate, land use shifts, socioeconomic development, and political decisions have had a tremendous impact on the spatial and temporal variation of soil carbon. How soil carbon interacts with such changing natural environmental and anthropogenic forcings within various ecosystem domains and spatial and temporal scales is still poorly understood. We discern different paradigms to model soil carbon and explore the meaning of such diversity in soil carbon paradigms situated within digital soil mapping (DSM) and beyond. The Meta Soil Model offers a container to hold multiple modeling paradigms that generate a variety of soil carbon realizations. The term soil realization acknowledges that there is not only one ‘soil carbon map’ or ‘soil carbon model’, but also several possible ones that approximate reality. The Meta Soil Model allows integrating, fusing, and synthesizing various soil carbon observations/maps/models through laboratory, field, or proximal/remote methods and ensembles other integration methods aiming to create more holistic representations of soil carbon. Besides explicit integration of soil carbon data/maps/models, the Meta Soil Model also facilitates side-by-side comparisons in a consistent and coherent framework. Here, we present a multiplicity of different DSM and modeling approaches and how they are integrated into a Meta Soil Carbon Model. Each approach is exemplified by a coherent model that entails the full suite of classical steps adopted in DSM to: (1) identify research questions and model approach, (2) develop a sampling design, (3) collect soil carbon data, (4) collect ancillary data in environmental and human domains, (5) analyze data (modeling), (6) create soil carbon predictions, estimates, or simulations and their uncertainties, and (7) test and validate soil carbon models. We present the integration pathways to build each of the exemplified Meta Soil Carbon Models. In conclusion, soil carbon can be viewed through various lenses- from above (through remote and/or proximal sensing), below (a soil pit or petri dish in the laboratory), or sideways (i.e., in new ways integrating multiple approaches). DSM and modeling is shifted into a new phase that is pluralistic in nature embracing a multiplicity of pathways focused to integrate data, methods, and knowledge and to understand about soils and ecosystems. In that sense, it is becoming more and more inter- and transdisciplinary, and through multiple comparisons, adaptations and validations, more robust, reliable and useful. MenosOver the past decades, a changing climate, land use shifts, socioeconomic development, and political decisions have had a tremendous impact on the spatial and temporal variation of soil carbon. How soil carbon interacts with such changing natural environmental and anthropogenic forcings within various ecosystem domains and spatial and temporal scales is still poorly understood. We discern different paradigms to model soil carbon and explore the meaning of such diversity in soil carbon paradigms situated within digital soil mapping (DSM) and beyond. The Meta Soil Model offers a container to hold multiple modeling paradigms that generate a variety of soil carbon realizations. The term soil realization acknowledges that there is not only one ‘soil carbon map’ or ‘soil carbon model’, but also several possible ones that approximate reality. The Meta Soil Model allows integrating, fusing, and synthesizing various soil carbon observations/maps/models through laboratory, field, or proximal/remote methods and ensembles other integration methods aiming to create more holistic representations of soil carbon. Besides explicit integration of soil carbon data/maps/models, the Meta Soil Model also facilitates side-by-side comparisons in a consistent and coherent framework. Here, we present a multiplicity of different DSM and modeling approaches and how they are integrated into a Meta Soil Carbon Model. Each approach is exemplified by a coherent model that entails the full suite of classica... Mostrar Tudo |
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Palavras-Chave: |
Carbono orgânico do solo; Mapeamento digital de solos; Modelo meta solo; Modelos de solos; Paradigmas. |
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Thesagro: |
Fusão; Integração. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 03589naa a2200313 a 4500
001 2051680
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008 2016 bl uuuu u00u1 u #d
100 1 $aGRUNWALD, S.
245 $aThe meta soil model$ban integrative framework to model soil carbon across various ecosystems and scales.$h[electronic resource]
260 $c2016
520 $aOver the past decades, a changing climate, land use shifts, socioeconomic development, and political decisions have had a tremendous impact on the spatial and temporal variation of soil carbon. How soil carbon interacts with such changing natural environmental and anthropogenic forcings within various ecosystem domains and spatial and temporal scales is still poorly understood. We discern different paradigms to model soil carbon and explore the meaning of such diversity in soil carbon paradigms situated within digital soil mapping (DSM) and beyond. The Meta Soil Model offers a container to hold multiple modeling paradigms that generate a variety of soil carbon realizations. The term soil realization acknowledges that there is not only one ‘soil carbon map’ or ‘soil carbon model’, but also several possible ones that approximate reality. The Meta Soil Model allows integrating, fusing, and synthesizing various soil carbon observations/maps/models through laboratory, field, or proximal/remote methods and ensembles other integration methods aiming to create more holistic representations of soil carbon. Besides explicit integration of soil carbon data/maps/models, the Meta Soil Model also facilitates side-by-side comparisons in a consistent and coherent framework. Here, we present a multiplicity of different DSM and modeling approaches and how they are integrated into a Meta Soil Carbon Model. Each approach is exemplified by a coherent model that entails the full suite of classical steps adopted in DSM to: (1) identify research questions and model approach, (2) develop a sampling design, (3) collect soil carbon data, (4) collect ancillary data in environmental and human domains, (5) analyze data (modeling), (6) create soil carbon predictions, estimates, or simulations and their uncertainties, and (7) test and validate soil carbon models. We present the integration pathways to build each of the exemplified Meta Soil Carbon Models. In conclusion, soil carbon can be viewed through various lenses- from above (through remote and/or proximal sensing), below (a soil pit or petri dish in the laboratory), or sideways (i.e., in new ways integrating multiple approaches). DSM and modeling is shifted into a new phase that is pluralistic in nature embracing a multiplicity of pathways focused to integrate data, methods, and knowledge and to understand about soils and ecosystems. In that sense, it is becoming more and more inter- and transdisciplinary, and through multiple comparisons, adaptations and validations, more robust, reliable and useful.
650 $aFusão
650 $aIntegração
653 $aCarbono orgânico do solo
653 $aMapeamento digital de solos
653 $aModelo meta solo
653 $aModelos de solos
653 $aParadigmas
700 1 $aCHAIKAEW, P.
700 1 $aCAO, B.
700 1 $aXIONG, X.
700 1 $aVASQUES, G. M.
700 1 $aKIM, J.
700 1 $aROSS, C. W.
700 1 $aCLINGENSMITH, C. M.
700 1 $aXU, Y.
700 1 $aGAVILAN, C.
773 $tIn: ZHANG, G.-L.; BRUS, D.; LIU, F.; SONG, X.-D.; LAGACHERIE, P. (Ed.). Digital soil mapping across paradigms, scales and boundaries. New York: Springer, 2016. cap. 14, p. 165-179.
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