COMPARISON OF KRIGING AND INVERSE-DISTANCE METHODS FOR MAPPING SOIL PARAMETERS

Variable-rate technology may provide a means of increasing fertilizer use efficiency by matching applications to specific conditions at a gi ven field location. Effective implementation of this technology depend s on accurately characterizing the spatial variability of soil paramet ers used to define the application rate. Kriging and inverse-distance- squared are two commonly used techniques for characterizing this spati al variability and interpolating between sampled points. To assess the accuracy of these techniques, data sets obtained from grid sampling t wo field research sites were used in a prediction-validation compariso n of ordinary kriging and inverse-distance methods using powers p = 1, 2, and 4. The accuracy of the inverse-distance methods tended to incr ease with the power of distance for data sets with a coefficient of va riation less than about 25% (typical of soil organic matter). However, for data sets with greater variation (such as soil NO3-), inverse-dis tance prediction methods using high distance powers (2 or 4) can give very inaccurate predictions. The accuracy of predictions from kriging was generally unaffected by the coefficient of variation, and was rela tively high for all of the sampling configurations considered in this study. These tendencies were also observed using 48- and 72-m subsampl es, although the use of wider sampling spacings greatly reduced the in formation in the maps constructed by each method. Careful thought shou ld be given to the choice of sample spacing and interpolation method t o be used before data are collected. Summary statistics, and the coeff icient of variation in particular, are simple measures that ran give a n indication of the relative accuracy of the inverse-distance and krig ing mapping approaches.