Determinación de la dependencia espacial mediante variogramas
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En este trabajo se realiza una introducción a la geoestadística, centrándose especialmente en el concepto de variograma, estructura que cuantifica la dependencia espacial, y el método de interpolación espacial Kriging. Para ello se exponen las bases teóricas de la dependencia espacial como fundamento para el desarrollo del variograma, incluyendo la concepción experimental pero también teórica del mismo, así como los distintos modelos existentes y razones por las que puede no modelizar correctamente la dependencia espacial. A continuación se presenta la teoría detrás del método de interpolación Kriging, junto con las diferentes variantes del modelo: el ordinario, el universal y el multivariante. Finalmente, se presenta un caso práctico que plasma la utilidad de estos conceptos con el fin de modelar, mediante las librerías gstat y sm de R, la interpolación de los contaminantes SO₂, PM₁₀ y NOₓ en el territorio gallego.
This work provides an introduction to geostatistics, focusing particularly on the concept of the variogram, a structure that quantifies spatial dependence, and the Kriging spatial interpolation method. To this end, the theoretical foundations of spatial dependence are presented as the basis for the development of the variogram, including both its experimental and theoretical conception, as well as the different existing models and the reasons why it may fail to properly model spatial dependence. Next, the theory behind the Kriging interpolation method is introduced, along with its different variants: ordinary, universal, and multivariate Kriging. Finally, a practical case is presented to illustrate the usefulness of these concepts, aiming to model the interpolation of the pollutants SO₂, PM₁₀ and NOₓ in the Galician territory using the R libraries gstat and sm.
This work provides an introduction to geostatistics, focusing particularly on the concept of the variogram, a structure that quantifies spatial dependence, and the Kriging spatial interpolation method. To this end, the theoretical foundations of spatial dependence are presented as the basis for the development of the variogram, including both its experimental and theoretical conception, as well as the different existing models and the reasons why it may fail to properly model spatial dependence. Next, the theory behind the Kriging interpolation method is introduced, along with its different variants: ordinary, universal, and multivariate Kriging. Finally, a practical case is presented to illustrate the usefulness of these concepts, aiming to model the interpolation of the pollutants SO₂, PM₁₀ and NOₓ in the Galician territory using the R libraries gstat and sm.
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