Geostatistical methods to identify and map spatial variations of soil salinity
Impacto
Scholar |
Otros documentos de la autoría: Juan, Pablo; Mateu, Jorge; Jordán Vidal, Manuel Miguel; Mataix-Solera, Jorge; Meléndez-Pastor, I.; Navarro Pedreño, José
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/43662
comunitat-uji-handle3:10234/43643
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http://dx.doi.org/10.1016/j.gexplo.2010.10.003 |
Metadatos
Título
Geostatistical methods to identify and map spatial variations of soil salinityAutoría
Fecha de publicación
2011-01Editor
ElsevierISSN
0375-6742Cita bibliográfica
Journal of Geochemical Exploration Volume 108, Issue 1, January 2011Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0375674210001482Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
The problem of estimating and predicting spatial distribution of a spatial stochastic process, observed at irregular locations in space, is considered in this paper. Environmental variables usually show spatial ... [+]
The problem of estimating and predicting spatial distribution of a spatial stochastic process, observed at irregular locations in space, is considered in this paper. Environmental variables usually show spatial dependencies among observations, with lead one to use geostatisticalmethods to model the spatial distributions of those observations. This is particularly important in the study of soil properties and their spatial variability. In this study geostatistical techniques were used to describe the spatial dependence and to quantify the scale and intensity of spatialvariations of soil properties, which provide the essential spatial information for local estimation. In this contribution, we propose a spatial Gaussian linear mixed model that involves (a) a non-parametric term for accounting deterministic trend due to exogenous variables and (b) a parametric component for defining the purely spatial random variation due possibly to latent spatial processes. We focus here on the analysis of the relationship between soil electrical conductivity and Na content to identifyspatialvariations of soilsalinity. This analysis can be useful for agricultural and environmental land management. [-]
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