Orbital and laboratory spectral data to optimize soil analysis

Detalhes bibliográficos
Autor(a) principal: Fiorio, Peterson Ricardo
Data de Publicação: 2009
Outros Autores: Demattê, José Alexandre M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Scientia Agrícola (Online)
Texto Completo: https://www.revistas.usp.br/sa/article/view/22448
Resumo: Traditional soil analyses are time-consuming with high cost and environmental risks, thus the use of new technologies such as remote sensing have to be estimulated. The purpose of this work was to quantify soil attributes by laboratory and orbital sensors as a non-destructive and a non-pollutant method. The study area was in the region of Barra Bonita, state of São Paulo, Brazil, in a 473 ha bare soil area. A sampling grid was established (100 × 100 m), with a total of 474 locations and a total of 948 soil samples. Each location was georeferenced and soil samples were collected for analysis. Reflectance data for each soil sample was measured with a laboratory sensor (450 to 2,500 nm). For the same locations, reflectance data was obtained from a TM-Landsat-5 image. Multiple linear regression equations were developed for 50% of the samples. Two models were developed: one for spectroradiometric laboratory data and the second for TM-Landsat-5 orbital data. The remaining 50% of the samples were used to validate the models. The test compared the attribute content quantified by the spectral models and that determined in the laboratory (conventional methods). The highest coefficients of determination for the laboratory data were for clay content (R² = 0.86) and sand (R² = 0.82) and for the orbital data (R² = 0.61 and 0.63, respectively). By using the present methodology, it was possible to estimate CEC (R² = 0.64) by the laboratory sensor. Laboratory and orbital sensors can optimize time, costs and environment pollutants when associated with traditional soil analysis.
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spelling Orbital and laboratory spectral data to optimize soil analysis Dados espectrais orbitais e de laboratório na otimização da análise do solo remote sensingsoil attributessoil reflectancesensoriamento remotoatributos do soloreflectância do solo Traditional soil analyses are time-consuming with high cost and environmental risks, thus the use of new technologies such as remote sensing have to be estimulated. The purpose of this work was to quantify soil attributes by laboratory and orbital sensors as a non-destructive and a non-pollutant method. The study area was in the region of Barra Bonita, state of São Paulo, Brazil, in a 473 ha bare soil area. A sampling grid was established (100 × 100 m), with a total of 474 locations and a total of 948 soil samples. Each location was georeferenced and soil samples were collected for analysis. Reflectance data for each soil sample was measured with a laboratory sensor (450 to 2,500 nm). For the same locations, reflectance data was obtained from a TM-Landsat-5 image. Multiple linear regression equations were developed for 50% of the samples. Two models were developed: one for spectroradiometric laboratory data and the second for TM-Landsat-5 orbital data. The remaining 50% of the samples were used to validate the models. The test compared the attribute content quantified by the spectral models and that determined in the laboratory (conventional methods). The highest coefficients of determination for the laboratory data were for clay content (R² = 0.86) and sand (R² = 0.82) and for the orbital data (R² = 0.61 and 0.63, respectively). By using the present methodology, it was possible to estimate CEC (R² = 0.64) by the laboratory sensor. Laboratory and orbital sensors can optimize time, costs and environment pollutants when associated with traditional soil analysis. Analises de solos tradicionais consomem tempo com alto custo e riscos ambientais. Dessa forma, o uso de novas tecnologias como o sensoriamento remoto tem sido estimulado. O objetivo do trabalho foi quantificar atributos dos solos por um método não destrutivo e não poluente utilizando sensor de laboratório e orbital. A área de estudo localiza-se na região de Barra Bonita, Brasil, com 473 ha com solo exposto. Foi estabelecida uma malha de amostragem (100 m × 100 m) com 474 pontos de amostragem e um total de 948 amostras de solos. Os pontos de amostragem foram georreferenciados, e amostras de solos coletadas e enviadas para análises. Os dados de Reflectância foram obtidos para cada amostra de solo com o sensor em laboratório (450 a 2500 nm). Nos mesmos locais de amostragem de solos, foram obtidos dados de reflectância de imagens orbitais TM-Landsat-5. Equações lineares de regressão múltiplas foram desenvolvidas com 50% das amostras. Dois modelos foram desenvolvidos: o primeiro com dados de espectroradiometria de laboratório e o segundo para os dados orbitais da imagem TM Landsat-5. O restante das amostras, 50% foram utilizadas para validar o modelo. O teste comparou os valores dos atributos quantificados pelos modelos espectrais e os determinados em laboratório (método convencional). Os maiores coeficientes de determinação para os resultados de laboratório foram para argila (R² = 0,86) e areia (R² = 0,82) e para os dados orbitais (R² 0,61 e 0,63, respectivamente). Também foi possível com o presente método estimar CTC (R² = 0,64) para o sensor de laboratório, podendo otimizar tempo, custos e poluições ambientais associadas com as análises de solos tradicionais. Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz2009-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.revistas.usp.br/sa/article/view/2244810.1590/S0103-90162009000200015Scientia Agricola; v. 66 n. 2 (2009); 250-257Scientia Agricola; Vol. 66 No. 2 (2009); 250-257Scientia Agricola; Vol. 66 Núm. 2 (2009); 250-2571678-992X0103-9016reponame:Scientia Agrícola (Online)instname:Universidade de São Paulo (USP)instacron:USPenghttps://www.revistas.usp.br/sa/article/view/22448/24472Copyright (c) 2015 Scientia Agricolainfo:eu-repo/semantics/openAccessFiorio, Peterson RicardoDemattê, José Alexandre M.2015-07-07T18:38:54Zoai:revistas.usp.br:article/22448Revistahttp://revistas.usp.br/sa/indexPUBhttps://old.scielo.br/oai/scielo-oai.phpscientia@usp.br||alleoni@usp.br1678-992X0103-9016opendoar:2015-07-07T18:38:54Scientia Agrícola (Online) - Universidade de São Paulo (USP)false
dc.title.none.fl_str_mv Orbital and laboratory spectral data to optimize soil analysis
Dados espectrais orbitais e de laboratório na otimização da análise do solo
title Orbital and laboratory spectral data to optimize soil analysis
spellingShingle Orbital and laboratory spectral data to optimize soil analysis
Fiorio, Peterson Ricardo
remote sensing
soil attributes
soil reflectance
sensoriamento remoto
atributos do solo
reflectância do solo
title_short Orbital and laboratory spectral data to optimize soil analysis
title_full Orbital and laboratory spectral data to optimize soil analysis
title_fullStr Orbital and laboratory spectral data to optimize soil analysis
title_full_unstemmed Orbital and laboratory spectral data to optimize soil analysis
title_sort Orbital and laboratory spectral data to optimize soil analysis
author Fiorio, Peterson Ricardo
author_facet Fiorio, Peterson Ricardo
Demattê, José Alexandre M.
author_role author
author2 Demattê, José Alexandre M.
author2_role author
dc.contributor.author.fl_str_mv Fiorio, Peterson Ricardo
Demattê, José Alexandre M.
dc.subject.por.fl_str_mv remote sensing
soil attributes
soil reflectance
sensoriamento remoto
atributos do solo
reflectância do solo
topic remote sensing
soil attributes
soil reflectance
sensoriamento remoto
atributos do solo
reflectância do solo
description Traditional soil analyses are time-consuming with high cost and environmental risks, thus the use of new technologies such as remote sensing have to be estimulated. The purpose of this work was to quantify soil attributes by laboratory and orbital sensors as a non-destructive and a non-pollutant method. The study area was in the region of Barra Bonita, state of São Paulo, Brazil, in a 473 ha bare soil area. A sampling grid was established (100 × 100 m), with a total of 474 locations and a total of 948 soil samples. Each location was georeferenced and soil samples were collected for analysis. Reflectance data for each soil sample was measured with a laboratory sensor (450 to 2,500 nm). For the same locations, reflectance data was obtained from a TM-Landsat-5 image. Multiple linear regression equations were developed for 50% of the samples. Two models were developed: one for spectroradiometric laboratory data and the second for TM-Landsat-5 orbital data. The remaining 50% of the samples were used to validate the models. The test compared the attribute content quantified by the spectral models and that determined in the laboratory (conventional methods). The highest coefficients of determination for the laboratory data were for clay content (R² = 0.86) and sand (R² = 0.82) and for the orbital data (R² = 0.61 and 0.63, respectively). By using the present methodology, it was possible to estimate CEC (R² = 0.64) by the laboratory sensor. Laboratory and orbital sensors can optimize time, costs and environment pollutants when associated with traditional soil analysis.
publishDate 2009
dc.date.none.fl_str_mv 2009-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://www.revistas.usp.br/sa/article/view/22448
10.1590/S0103-90162009000200015
url https://www.revistas.usp.br/sa/article/view/22448
identifier_str_mv 10.1590/S0103-90162009000200015
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://www.revistas.usp.br/sa/article/view/22448/24472
dc.rights.driver.fl_str_mv Copyright (c) 2015 Scientia Agricola
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 Scientia Agricola
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
publisher.none.fl_str_mv Universidade de São Paulo. Escola Superior de Agricultura Luiz de Queiroz
dc.source.none.fl_str_mv Scientia Agricola; v. 66 n. 2 (2009); 250-257
Scientia Agricola; Vol. 66 No. 2 (2009); 250-257
Scientia Agricola; Vol. 66 Núm. 2 (2009); 250-257
1678-992X
0103-9016
reponame:Scientia Agrícola (Online)
instname:Universidade de São Paulo (USP)
instacron:USP
instname_str Universidade de São Paulo (USP)
instacron_str USP
institution USP
reponame_str Scientia Agrícola (Online)
collection Scientia Agrícola (Online)
repository.name.fl_str_mv Scientia Agrícola (Online) - Universidade de São Paulo (USP)
repository.mail.fl_str_mv scientia@usp.br||alleoni@usp.br
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