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Registro Completo
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Biblioteca(s): |
Epagri-Sede. |
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Data corrente: |
10/01/2019 |
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Data da última atualização: |
10/01/2019 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
DEMATTÊ, J. A. M.; DOTTO, A. C.; SILVEIRA, A. F. D.; SATO, M. V.; DALMOLIN, R. S. D.; ARAÚJO, M. S. B.; SILVA, E. B.; NANNI, M. R.; NORONHA, N. C.; LACERDA, M. P. C.; ARAÚJO FILHO, J. C.; RIZZO, R. |
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Título: |
The Brazilian Soil Spectral Library (BSSL): a general overview. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Abstracts... Viçosa: Sociedade Brasileira de Ciência do Solo, 2018. |
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Idioma: |
Inglês |
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Conteúdo: |
The Brazilian Soil Spectral Library (BSSL) began its collection in 1995 at the Department of Soil
Science (ESALQ-USP). Currently, SSLB has gathered data from all the 26 States of Brazil, reaching
more than 38,000 soil samples. This achievement was only possible to reach due to the
collaboration (33instituitions) and 49 researchers. The objective of this manuscript is to present the
system on the utilization and applications of this dataset. The spectral data range from visible to
shortwave infrared (350 to 2.500 nm). The BSSL allow identify the main spectral behavior of
Brazilian soils. With the development of BSSL, it is possible to: a) locate partners for joint research
development; b) assess, via internet, whether a local, regional, or national estimative of your own
spectra, based on calibrated models. In this context, we also can perform the prediction of soil color
by using the reflectance data. In the present work, we determined how many spectral patterns are
required to represent Brazilian soils. The preliminary results showed that 5 spectral curves can
represent the spectral patterns of Brazilian soils. The BSSL can be informative regarding
classification, soil surveys and quantification. It will be presented the utility of national spectra to
predict soil attributes, such as organic matter (OM), sand, silt, clay, cation exchange capacity (CEC),
and pH. The result of national estimation model for these attributes showed that the granulometry
presented good performances (R2between 0.55 and 0.70) and slightly smaller for OM, CEC and pH.
New contributions to the BSSL are still encouraged for a second round for 2019. We hope that this
work reinvigorate our community's discussion towards the importance of sensors in agriculture,
environment and extend the soil researches. MenosThe Brazilian Soil Spectral Library (BSSL) began its collection in 1995 at the Department of Soil
Science (ESALQ-USP). Currently, SSLB has gathered data from all the 26 States of Brazil, reaching
more than 38,000 soil samples. This achievement was only possible to reach due to the
collaboration (33instituitions) and 49 researchers. The objective of this manuscript is to present the
system on the utilization and applications of this dataset. The spectral data range from visible to
shortwave infrared (350 to 2.500 nm). The BSSL allow identify the main spectral behavior of
Brazilian soils. With the development of BSSL, it is possible to: a) locate partners for joint research
development; b) assess, via internet, whether a local, regional, or national estimative of your own
spectra, based on calibrated models. In this context, we also can perform the prediction of soil color
by using the reflectance data. In the present work, we determined how many spectral patterns are
required to represent Brazilian soils. The preliminary results showed that 5 spectral curves can
represent the spectral patterns of Brazilian soils. The BSSL can be informative regarding
classification, soil surveys and quantification. It will be presented the utility of national spectra to
predict soil attributes, such as organic matter (OM), sand, silt, clay, cation exchange capacity (CEC),
and pH. The result of national estimation model for these attributes showed that the granulometry
presented good performan... Mostrar Tudo |
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Palavras-Chave: |
big data; environment; library; remote sensing; soil mapping; soil sensing. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
LEADER 02766naa a2200325 a 4500
001 1128203
005 2019-01-10
008 2018 bl uuuu u00u1 u #d
100 1 $aDEMATTÊ, J. A. M.
245 $aThe Brazilian Soil Spectral Library (BSSL)$ba general overview.$h[electronic resource]
260 $c2018
520 $aThe Brazilian Soil Spectral Library (BSSL) began its collection in 1995 at the Department of Soil Science (ESALQ-USP). Currently, SSLB has gathered data from all the 26 States of Brazil, reaching more than 38,000 soil samples. This achievement was only possible to reach due to the collaboration (33instituitions) and 49 researchers. The objective of this manuscript is to present the system on the utilization and applications of this dataset. The spectral data range from visible to shortwave infrared (350 to 2.500 nm). The BSSL allow identify the main spectral behavior of Brazilian soils. With the development of BSSL, it is possible to: a) locate partners for joint research development; b) assess, via internet, whether a local, regional, or national estimative of your own spectra, based on calibrated models. In this context, we also can perform the prediction of soil color by using the reflectance data. In the present work, we determined how many spectral patterns are required to represent Brazilian soils. The preliminary results showed that 5 spectral curves can represent the spectral patterns of Brazilian soils. The BSSL can be informative regarding classification, soil surveys and quantification. It will be presented the utility of national spectra to predict soil attributes, such as organic matter (OM), sand, silt, clay, cation exchange capacity (CEC), and pH. The result of national estimation model for these attributes showed that the granulometry presented good performances (R2between 0.55 and 0.70) and slightly smaller for OM, CEC and pH. New contributions to the BSSL are still encouraged for a second round for 2019. We hope that this work reinvigorate our community's discussion towards the importance of sensors in agriculture, environment and extend the soil researches.
653 $abig data
653 $aenvironment
653 $alibrary
653 $aremote sensing
653 $asoil mapping
653 $asoil sensing
700 1 $aDOTTO, A. C.
700 1 $aSILVEIRA, A. F. D.
700 1 $aSATO, M. V.
700 1 $aDALMOLIN, R. S. D.
700 1 $aARAÚJO, M. S. B.
700 1 $aSILVA, E. B.
700 1 $aNANNI, M. R.
700 1 $aNORONHA, N. C.
700 1 $aLACERDA, M. P. C.
700 1 $aARAÚJO FILHO, J. C.
700 1 $aRIZZO, R.
773 $tIn: WORLD CONGRESS OF SOIL SCIENCE, 21., 2018, Rio de Janeiro. Abstracts... Viçosa: Sociedade Brasileira de Ciência do Solo, 2018.
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