The clay minerals goethite and hematite are iron oxides serving as indicators of the soil environment, with great influence on the soil physical and chemical properties. Knowledge of spatial patterns of these oxides can help understand the interrelationships of cause and effect with soil properties. In this sense, the quality of the spatial estimates can affect the results and consequently the interpretation of the spatial patterns. This study aimed to evaluate the performance of the geostatistical estimation methods by ordinary kriging (OK) and conditional stochastic simulations (SGS) in the characterization of spatial concentration of the iron oxides goethite (Gt) and hematite (Hm) in a concave and in a convex landform. From each landform, 121 soil samples of an Alfisol were collected at points with a regular spacing of 10 m. The iron oxide content was obtained by X-ray diffraction. The data were subjected to geostatistical analysis by modeling the variogram and later interpolation by OK and SGS. The OK did not reflect the true variability of the iron oxides hematite and goethite and is therefore inappropriate for the spatial characterization of the iron oxide concentrations. Thus, the use of SGS is preferable to kriging when the maintenance of high and low values in the spatial estimates is required. The performance of the geostatistical methods was influenced by the landform. For iron oxides, E-type maps should be recommended instead of OK maps, for being rich in detail and practical to define homogenous zones for localized managing for OK, particularly in concave landforms.
goethite; hematite; ordinary kriging; accuracy; pedometry
