To make reliable interpretations on the sparse spatial data, the spatial distribution characteristics that are inevitable for spatial estimation should be properly analyzed. Variograms have been widely used for obtaining the spatial characteristics inherent to data in spatial estimation problems. But their applications were limited as the basic information for further data estimation. Therefore, the additional analysis of the meaning of variograms is required for more reliable data processing and interpretations. In this paper, we investigated the proper meaning of variogram values and the specific features of distributions which can be obtained through variogram analysis. Variograms can provide the information on both linearity and the strength changes of interrelationships between the data sets according to the direction and lag distance. First, sill and range values, which are main parameters of variograms, were analyzed. Then a similarity range using spatial auto-correlation values was introduced to verify the applicability of linearity analysis through the comparative study of spatial distribution features of gravity and magnetic data collected in Hwasan caldera. Through these analyses, we were able to identify the dissimilar patterns of gravity and magnetic data that became apparent according to the distribution and variation ranges of the data sets. It is inferred that the gravity and magnetic anomalous bodies are extended to the ground because linearity direction of gravity and magnetic data appear similarly with linearity derection of topography in Hwasan caldera.