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Resumen
Soil texture is determined by the parent material of the soil and the resulting pedogenetic processes. Because the spatial distribution of soil texture governs several soil physical and ofsoil profile database generate textural soil class map for the same soil dpths; and describe the distribution of soil texture in relation to different landscape units. We used 4663 soil texture observations and 64 environmental covariates to represent the soil forming [ver mas...]
dc.contributor.authorSchulz, Guillermo
dc.contributor.authorRodriguez, Dario Martin
dc.contributor.authorAngelini, Marcos Esteban
dc.contributor.authorMoretti, Lucas Martin
dc.contributor.authorOlmedo, Guillermo Federico
dc.contributor.authorTenti Vuegen, Leonardo Mauricio
dc.contributor.authorColazo, Juan Cruz
dc.contributor.authorGuevara, Mario
dc.contributor.editorZinck, Joseph Alfred
dc.contributor.editorMetternicht, Graciela
dc.contributor.editordel Valle, Héctor Francisco
dc.contributor.editorAngelini, Marcos Esteban
dc.date.accessioned2023-03-17T10:20:25Z
dc.date.available2023-03-17T10:20:25Z
dc.date.issued2023-01
dc.identifier.issn978-3031-20666-5
dc.identifier.otherhttps://doi.org/10.1007/978-3-031-20667-2_14
dc.identifier.urihttp://hdl.handle.net/20.500.12123/14260
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-031-20667-2_14
dc.description.abstractSoil texture is determined by the parent material of the soil and the resulting pedogenetic processes. Because the spatial distribution of soil texture governs several soil physical and ofsoil profile database generate textural soil class map for the same soil dpths; and describe the distribution of soil texture in relation to different landscape units. We used 4663 soil texture observations and 64 environmental covariates to represent the soil forming factors (e.g., remote sensing data, climate data of geomorphology map). We modelled clay, silt, and sand at 0-15, 15-30, 30-60 and 60-100 cm, fraction. and empirical relationship with environmental covariates using Random Forest to predict their spatial distribution. Finally we performance an analysis of uncertainty through repeated cross – validation. We observed model efficiency coefficient (MEC) value between 0.452 and 0.557, with and RMSE between 8.77% and 11.21% for the clay fraction. The MEC for the silt fraction ranged from 0.561 to 0.638 with and RMSE of 10.50% to 12.01% for sand fraction the MEC ranged from 0.587 to 0.640 with RMSE values between 16.19% and 16.76%. The general patterns of uncertainty are consistent with areas of limited data. Our resulys increased the quality, quantity and accessibility of information on soil texture in Argentina by providing new insights into both the distribution of parent materials and the intensity of pedogenetic processes in each region.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherSpringeres_AR
dc.relationinfo:eu-repograntAgreement/INTA/PNSUELO-1134032/AR./Bases conceptuales y nuevas herramientas para la cartografía de suelos.
dc.relationinfo:eu-repograntAgreement/INTA/2019-RIST-E2-I051-001/2019-RIST-E2-I051-001/AR./Cartografía y evaluación de tierras
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/es_AR
dc.sourceGeopedology. An Integration of Geomorphology and Pedology for Soil and Landscape Studies / Editors: Joseph Alfred Zinck, Graciela Metternicht, Héctor Francisco del Valle, Marcos Angelini. Springer, 2023. Chapter 14. p. 263-281es_AR
dc.subjectSoil Mapseng
dc.subjectMapa Edafológicoes_AR
dc.subjectClayeng
dc.subjectArcillases_AR
dc.subjectSilteng
dc.subjectLimoes_AR
dc.subjectSandeng
dc.subjectArenaes_AR
dc.subjectSoil Textureeng
dc.subjectTextura del Sueloes_AR
dc.subject.otherDigital Soil Mapeng
dc.subject.otherMapa Digital de Sueloses_AR
dc.subject.otherSoil Layerseng
dc.subject.otherCapas del Sueloes_AR
dc.titleDigital soil texture map of Argentina and their relationship to soil - forming factors and processeses_AR
dc.typeinfo:ar-repo/semantics/parte de libroes_AR
dc.typeinfo:eu-repo/semantics/bookPartes_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)es_AR
dc.description.filFil: Schulz, Guillermo A. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentinaes_AR
dc.description.filFil: Rodriguez, Darío M. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentinaes_AR
dc.description.filFil: Angelini, Marcos Esteban. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentina. Food and Agriculture Organization on the UN Global soil Partnership; Italia. Universidad Nacional de Lujan. Departamento de Ciencias Básicas; Argentinaes_AR
dc.description.filFil: Moretti, Lucas M. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Cerro Azul; Argentinaes_AR
dc.description.filFil: Olmedo, Guillermo Federico. Food and Agriculture Organization on the UN Global soil Partnership; Italia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Mendoza; Argentinaes_AR
dc.description.filFil: Tenti Vuegen, Leonardo Mauricio. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos; Argentinaes_AR
dc.description.filFil: Colazo, Juan Cruz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Luis; Argentinaes_AR
dc.description.filFil: Guevara, Mario. Universidad Nacional Autónoma de México. Campus Juriquilla. Centro de Geociencias; Méxicoes_AR
dc.subtypelibro


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