Prediction and mapping of soil attributes using diffuse reflectance spectroscopy and magnetic susceptibility

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dc.contributor.authorDe Souza Bahia, Angélica Santos Rabelo [UNESP]
dc.contributor.authorMarques, José [UNESP]
dc.contributor.authorLa Scala, Newton [UNESP]
dc.contributor.authorCerri, Carlos Eduardo Pellegrino
dc.contributor.authorCamargo, Livia Arantes [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2018-12-11T17:35:27Z
dc.date.available2018-12-11T17:35:27Z
dc.date.issued2017-11-01
dc.description.abstractThe development of fast, accurate and low-cost methods to quantify soil attributes is of paramount importance to enable detailed mapping, mainly in tropical regions where there is great variation of the chemical, physical and mineralogical attributes. Therefore, the aims of this paper were (i) to investigate if visible and near infrared (VIS-NIR) spectroscopy and magnetic susceptibility (MS) can be applied to determine soil attributes at the sandstone-basaltic transition and (ii) evaluate and map their spatial distribution. Calibration models based on VIS-NIR spectroscopy and MS were developed separately for each attribute. Soil samples (0-25 cm depth) were collected at 446 sites, air-dried and passed through a 2-mm sieve and analyzed in the laboratory. To develop models based on soil spectra and laboratory data, the partial least squares regression (PLSR) was used. Already, the MS-based models were calibrated by linear regression between magnetic and laboratory data. The best prediction accuracy parameters were obtained with MS, later with VIS-NIR and lastly with VIS. The more accurate results between the observed and predicted values were found for iron oxide extracted by dithionite (R2 = 0.89, RRMSE = 0.02), clay (R2 = 0.85, RRMSE = 0.76) and total carbon (R2 = 0.83, RRMSE = 1.18) estimated by MS, revealing that this is a good predictor of key properties of studied soils, even with wide chemical and mineralogical variation. Both tools are very attractive for the strategic planning of land use and occupation, mapping large areas with detailed scale, environmental monitoring and precision agriculture.en
dc.description.affiliationDep. of Soils and Fertilizers State Univ. of São Paulo (UNESP) Research Group CSME Soil Characterization for Specific Management
dc.description.affiliationDep. of Exact Sciences State Univ. of São Paulo (UNESP) Research Group CSME Soil Characterization for Specific Management
dc.description.affiliationDep. of Soil Science São Paulo Univ.
dc.description.affiliationUnespDep. of Soils and Fertilizers State Univ. of São Paulo (UNESP) Research Group CSME Soil Characterization for Specific Management
dc.description.affiliationUnespDep. of Exact Sciences State Univ. of São Paulo (UNESP) Research Group CSME Soil Characterization for Specific Management
dc.format.extent1450-1462
dc.identifierhttp://dx.doi.org/10.2136/sssaj2017.06.0206
dc.identifier.citationSoil Science Society of America Journal, v. 81, n. 6, p. 1450-1462, 2017.
dc.identifier.doi10.2136/sssaj2017.06.0206
dc.identifier.issn1435-0661
dc.identifier.issn0361-5995
dc.identifier.scopus2-s2.0-85040591269
dc.identifier.urihttp://hdl.handle.net/11449/179507
dc.language.isoeng
dc.relation.ispartofSoil Science Society of America Journal
dc.relation.ispartofsjr0,997
dc.rights.accessRightsAcesso restrito
dc.sourceScopus
dc.titlePrediction and mapping of soil attributes using diffuse reflectance spectroscopy and magnetic susceptibilityen
dc.typeArtigo

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