Multivariate mapping of soil with structural equation modelling
In a previous study we introduced structural equation modelling (SEM) for digital soil mapping in the Argentine Pampas. An attractive property of SEM is that it incorporates pedological knowledge explicitly through a mathematical implementation of a conceptual model. Many soil processes operate with...
| Autores principales: | , , |
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| Formato: | info:ar-repo/semantics/artículo |
| Lenguaje: | Inglés |
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2017
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12123/1668 http://onlinelibrary.wiley.com/doi/10.1111/ejss.12446/epdf |
| _version_ | 1855034835987333120 |
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| author | Angelini, Marcos Esteban Heuvelink, Gerard B.M. Kempen, Bas |
| author_browse | Angelini, Marcos Esteban Heuvelink, Gerard B.M. Kempen, Bas |
| author_facet | Angelini, Marcos Esteban Heuvelink, Gerard B.M. Kempen, Bas |
| author_sort | Angelini, Marcos Esteban |
| collection | INTA Digital |
| description | In a previous study we introduced structural equation modelling (SEM) for digital soil mapping in the Argentine Pampas. An attractive property of SEM is that it incorporates pedological knowledge explicitly through a mathematical implementation of a conceptual model. Many soil processes operate within the soil profile; therefore, SEM might be suitable for simultaneous prediction of soil properties for multiple soil layers. In this way, relations between soil properties in different horizons can be included that might result in more consistent predictions. The objectives of this study were therefore to apply SEM to multi-layer and multivariate soil mapping, and to test SEM functionality for suggestions to improve the modelling. We applied SEM to model and predict the lateral and vertical distribution of the cation exchange capacity (CEC), organic carbon (OC) and clay content of three major soil horizons, A, B and C, for a 23 000-km2 region in the Argentine Pampas. We developed a conceptual model based on pedological hypotheses. Next, we derived a mathematical model and calibrated it with environmental covariates and soil data from 320 soil profiles. Cross-validation of predicted soil properties showed that SEM explained only marginally more of the variance than a linear regression model. However, assessment of the covariation showed that SEM reproduces the covariance between variables much more accurately than linear regression. We concluded that SEM can be used to predict several soil properties in multiple layers by considering the interrelations between soil properties and layers. |
| format | info:ar-repo/semantics/artículo |
| id | INTA1668 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| record_format | dspace |
| spelling | INTA16682020-08-18T11:38:55Z Multivariate mapping of soil with structural equation modelling Angelini, Marcos Esteban Heuvelink, Gerard B.M. Kempen, Bas Suelo Soil Multivariate Analysis Cartography Análisis Multivariante Cartografía In a previous study we introduced structural equation modelling (SEM) for digital soil mapping in the Argentine Pampas. An attractive property of SEM is that it incorporates pedological knowledge explicitly through a mathematical implementation of a conceptual model. Many soil processes operate within the soil profile; therefore, SEM might be suitable for simultaneous prediction of soil properties for multiple soil layers. In this way, relations between soil properties in different horizons can be included that might result in more consistent predictions. The objectives of this study were therefore to apply SEM to multi-layer and multivariate soil mapping, and to test SEM functionality for suggestions to improve the modelling. We applied SEM to model and predict the lateral and vertical distribution of the cation exchange capacity (CEC), organic carbon (OC) and clay content of three major soil horizons, A, B and C, for a 23 000-km2 region in the Argentine Pampas. We developed a conceptual model based on pedological hypotheses. Next, we derived a mathematical model and calibrated it with environmental covariates and soil data from 320 soil profiles. Cross-validation of predicted soil properties showed that SEM explained only marginally more of the variance than a linear regression model. However, assessment of the covariation showed that SEM reproduces the covariance between variables much more accurately than linear regression. We concluded that SEM can be used to predict several soil properties in multiple layers by considering the interrelations between soil properties and layers. Fil: Angelini, Marcos Esteban. Wageningen University. Soil Geography and Landscape Group; Holanda. ISRIC — World Soil Information; Holanda. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Suelos;Argentina Fil: Heuvelink, G.B.M. Wageningen University. Soil Geography and Landscape Group; Holanda. ISRIC — World Soil Information; Holanda Fil: Kempen, B. ISRIC — World Soil Information; Holanda 2017-11-03T17:58:47Z 2017-11-03T17:58:47Z 2017-09 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/1668 http://onlinelibrary.wiley.com/doi/10.1111/ejss.12446/epdf 1351-0754 (Print) 1365-2389 (Online) DOI: 10.1111/ejss.12446 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf European Journal of Soil Science 68 (5) : 575–591 (September 2017) |
| spellingShingle | Suelo Soil Multivariate Analysis Cartography Análisis Multivariante Cartografía Angelini, Marcos Esteban Heuvelink, Gerard B.M. Kempen, Bas Multivariate mapping of soil with structural equation modelling |
| title | Multivariate mapping of soil with structural equation modelling |
| title_full | Multivariate mapping of soil with structural equation modelling |
| title_fullStr | Multivariate mapping of soil with structural equation modelling |
| title_full_unstemmed | Multivariate mapping of soil with structural equation modelling |
| title_short | Multivariate mapping of soil with structural equation modelling |
| title_sort | multivariate mapping of soil with structural equation modelling |
| topic | Suelo Soil Multivariate Analysis Cartography Análisis Multivariante Cartografía |
| url | http://hdl.handle.net/20.500.12123/1668 http://onlinelibrary.wiley.com/doi/10.1111/ejss.12446/epdf |
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