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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/113325
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dc.contributor.authorSilva, Alessandra Fagioli da-
dc.contributor.authorPereira, Maria Joao-
dc.contributor.authorCameiro, Joao Daniel-
dc.contributor.authorLopes Zimback, Celia Regina-
dc.contributor.authorBarbosa Landim, Paulo Milton-
dc.contributor.authorSoares, Amilcar-
dc.date.accessioned2014-12-03T13:11:36Z-
dc.date.accessioned2016-10-25T20:14:38Z-
dc.date.available2014-12-03T13:11:36Z-
dc.date.available2016-10-25T20:14:38Z-
dc.date.issued2014-05-01-
dc.identifierhttp://dx.doi.org/10.1016/j.geoderma.2013.12.011-
dc.identifier.citationGeoderma. Amsterdam: Elsevier Science Bv, v. 219, p. 106-116, 2014.-
dc.identifier.issn0016-7061-
dc.identifier.urihttp://hdl.handle.net/11449/113325-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/113325-
dc.description.abstractThis study presents a new approach to classifying types of soil based on the probability classes of the relevant set of attributes. Two key ideas are addressed in this study: (i) the use of stochastic simulations to generate a local cumulative distribution function or extreme classes of each attribute and (ii) the use of a multidimensional scaling (MDS) technique to visualize and quantify the relative importance of each attribute in the classification process. After the simulated realizations, the weighted distances attributes extreme values (probability classes) of each grid node are calculated and the MDS algorithm is applied for the spatial representation of the grid nodes in a new Cartesian reference frame based on the distances of the probability classes of attributes. This allows the classification of soil types based on the clusters in the MDS space, after expert validation. In the second step, a sensitivity analysis of the attributes is performed with MDS: each attribute is made neutral one at a time, by assuming the median rather than the extreme values in each grid node before the distance evaluation, and the consequent impact on the shape and centroid displacement of the clusters (soil types) in the MDS reference frame is calculated. Hence, the spatial uncertainty of the soil type/classes and the influence of various properties are evaluated in the MDS reference frame. This method is applied to soils in a region of Brazilian in which the previous classification of soil types has been a crucial tool for precision agriculture management. Using the MDS algorithm, the selected attributes (horizon, textural gradient, colors, saturation, sand content, and clay content) were represented in a two dimensional plot and grouped into eight clusters distinguished from each other by their characteristics. A sensitivity analysis shows that the horizon and saturation attributes had the greatest influence on determination of the clusters, i.e., the soil types. (c) 2014 Elsevier B.V. All rights reserved.en
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
dc.format.extent106-116-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.sourceWeb of Science-
dc.subjectDiagnostic attributesen
dc.subjectGeostatistical simulationen
dc.subjectMultidimensional scalingen
dc.subjectSoil mappingen
dc.titleA new approach to soil classification mapping based on the spatial distribution of soil propertiesen
dc.typeoutro-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionUniv Tecn Lisboa-
dc.description.affiliationUNESP Univ Estadual Paulista, Fac Ciencias Agron, Dept Recursos Nat, BR-18610307 Botucatu, SP, Brazil-
dc.description.affiliationUniv Tecn Lisboa, IST, CERENA, P-1049001 Lisbon, Portugal-
dc.description.affiliationUNESP Univ Estadual Paulista, Inst Geociencias & Ciencias Exatas, Dept Geol Aplicada, BR-13506900 Rio Claro, SP, Brazil-
dc.description.affiliationUnespUNESP Univ Estadual Paulista, Fac Ciencias Agron, Dept Recursos Nat, BR-18610307 Botucatu, SP, Brazil-
dc.description.affiliationUnespUNESP Univ Estadual Paulista, Inst Geociencias & Ciencias Exatas, Dept Geol Aplicada, BR-13506900 Rio Claro, SP, Brazil-
dc.identifier.doi10.1016/j.geoderma.2013.12.011-
dc.identifier.wosWOS:000333492400012-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofGeoderma-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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