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Influence of Spatial Structure on Accuracy of Interpolation Methods

Dep. of Crop and Soil Sciences, Michigan State Univ., East Lansing, MI 48824-1325

View larger version (13K): [in a new window]   Fig. 1. Sample variograms for the exhaustive simulated P data sets with nugget to sill (N/S) ratios of (a) 0.1, (b) 0.3, and (c) 0.6, respectively.

View larger version (91K): [in a new window]   Fig. 2. Example of an exhaustive data set obtained by simulated annealing from original soil samples (), grid points used for creating interpolated soil property maps (grid with 64 grid points and a 60-m distance between the grid points is used as an example) (•), and one of 100 test data sets consisting of 200 points randomly selected from the exhaustive data set (x) used to evaluate mapping accuracy.

View larger version (15K): [in a new window]   Fig. 3. The average G values obtained for each grid size based on 100 randomly selected test data sets plotted versus number of grid samples for P. Error bars represent standard deviations.

View larger version (13K): [in a new window]   Fig. 4. Sample variograms and variogram models for simulated data with low coefficient of variation (CV) and N/S ratio of 0.1 for (a) 529, (b) 225, (c) 144, and (d) 81 grid samples.