One of the basic principles of experimental design is blocking, which is an important factor in the treatment of the systematic spatial variability that can be found in the edaphic properties where agricultural experiments are conducted. Blocking has a mitigating or suppressing effect on the spatial dependence in the residuals of a model, something desirable in standard linear modeling, specifically in design models. Some computer programs yield a p value associated with the blocking effect in the analysis of variance table that in many cases has been incorrectly used to discard it, and although it may improve some properties of the analysis, it may affect the independence assumption required in several models. Therefore, the present research recommends the use of the H statistic associated with the corrected blocking efficiency to show the role of blocking in modeling with the incorporation of an additional advantage rarely considered related to the suppression or mitigation of spatial dependence. With the use of the Moran index, the spatial dependence of the residuals was studied in a simple factorial design in a completely randomized and blocking field layout, which evidenced the advantages of blocking in the mitigation or suppression of the spatial dependence despite the apparently little or no importance it seems to show in the analysis of variance table.

La estimación de los recursos del suelo a una escala diferente en las que se hacen las observaciones es un problema de importancia que sigue generando investigaciones relacionadas. Un aumento en la escala significa un aumento en la variación del parámetro, y esto puede causar problemas al interactuar con la no linealidad en un proceso o modelo. Cambiar la resolución espacial agregando o desagregando datos conlleva el riesgo de resultados contradictorios. Para demostrar este hecho se tomaron datos de Conductividad Eléctrica Aparente con el sensor EM38-MK2 en posición vertical al suelo de forma simultánea con los dos dipolos a dos profundidades relativas (0.75m y 1.5m), asociados a una misma coordenada. Se evaluaron tamaños de agregación espacial desde una rejilla de 5m´5m hasta 70m´70m, con razón aritmética de 5m. Se usaron coordenadas representativas para generar la matriz de pesos espaciales basada en el: i) centro de la grilla, ii) valor medio de las coordenadas que interceptan espacialmente cada celda, y iii) valor del centroide de los puntos agregados por cada celda. Para analizar el patrón de autocorrelación espacial se usó el índice de Moran Montecarlo para los residuales del modelo ajustado. Los resultados mostraron que a medida que se aumenta el tamaño de la rejilla, la dependencia espacial univariada comienza a disminuir para todas las coordenadas representativas, siendo la coordenada del centro de la celda la más afectada. Para una profundidad específica del sensor, se recomienda el uso de la coordenada del centroide y en agregaciones que superen los 20m para mantener la estructura de dependencia espacial que pudiera ser natural en esta variable y conveniente en procesos de modelado mediante regresión espacial.

The production of Voluntary Geographic Information has been growing considerably and continues to be an active area of research. However, the lack of knowledge about the quality of information generated on a voluntary and participatory basis raises challenges and questions about its use. In the review carried out for the Colombian case, no studies related to the subject were identified; consequently, this study is presented on the evaluation of the quality of this type of information on the road network of Bogotá with respect to completeness, positional accuracy and thematic accuracy. This evaluation was carried out by means of a semi-automatic process that uses a mobile buffer and the centroid of the roads to make the corresponding comparisons between two data sources. The results found reveal that the method used allowed to compare up to 85.0% of the data, and that the OpenStreetMap mesh has a completeness of 85.4%, over the entire area of Bogotá. A positional accuracy of 3.98 m and a thematic accuracy related to the percentage of error in the attributes: Road hierarchy, direction of flow and road naming of 35.8%, 15.0% and 34.6% respectively. The quality evaluated through completeness, positional and thematic accuracy in synergistic terms is deficient with respect to the minimum quality levels established in the standard data model, however, the evaluation for each of the attributes shows an acceptable quality in terms of completeness and thematic accuracy.

Aim of study: Our main objective was to take advantage of the ECa information that the EM38-MK2 sensor records simultaneously at two relative depths for modeling using spatial regression and the subsequent blocking of the conductivity estimate values, incorporating elevation. Area of study: A 23.1-ha field located in the municipality of Puerto López (Meta, Colombia). Material and methods: A series of georeferenced data (15438) was collected from the EM38-MK2 sensor, through which the ECa was obtained at two depths, a spatial aggregation was performed using a grid of 40 m  40 m (167 grid cells), to provide data in Lattice form, the centroid of the cells was determined as the new representative spatial coordinates, to adjust a Spatial Autoregression Model (SAC), and then define the blocks from the predictions of the adjusted model. Main results: The adjusted model has a comparative purpose with the usual proposals for delimiting management zones separately, so it was convenient to incorporate in the model a 3D weighting matrix relating the two relative depths recorded by the EM38MK2 sensor. By mapping the surface layer with the predictions of the SAC model, two distinguishable blocks were delimited in its ECa and management zone analyst (MZA), which can be suitable for experimentation or agricultural management. Research highlights: These results can be adopted to define the shape and dimension of the blocks in the context of experimental design so that with adequate blocking, the effect of spatial dependence associated with the physicochemical properties of soils related to ECa can be mitigated or suppressed.