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The present work aims to compare statistical models for reconstructing surfaces of spatially continuous phenomena by using a set of discrete samples taken over the study area. Four statistical models were considered: a geostatistical model, generalized additive models with this plate splines and tensor product splines as the choices of bidimensional smoothing functions and a bidimensional second order random walk model. Data consists of pH soil measurements taken at an area in the municipality of Xanxerê/SC. Predictions using the models are assessed and compared by three cross-validation measures: average prediction error, average absolute error and coverage levels. Overall better results were obtained with the geostatistical model followed by the generalized additive model with thin plate splines which is computationally atractive. Poor results were obtained with the other models which were unable to detect spatial variations on the soil pH values.

Comparação de Modelos para Reconstituição de Superfície de Valores de pH